import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import scipy
import sklearn
from scipy.stats import kurtosis, skew
from sklearn import metrics
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans , AgglomerativeClustering, DBSCAN
from sklearn.ensemble import RandomForestClassifier, VotingClassifier
from sklearn.linear_model import LogisticRegression, LogisticRegressionCV
from sklearn.model_selection import cross_val_score,StratifiedKFold, train_test_split,LeaveOneOut, GridSearchCV, KFold, RandomizedSearchCV
from sklearn.svm import SVC, NuSVC
from sklearn.neighbors import KNeighborsClassifier
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.metrics import confusion_matrix, classification_report, accuracy_score, f1_score, recall_score, precision_score
from skopt import BayesSearchCV
from skopt.space import Real, Integer, Categorical

import itertools

import os
import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
import torch.optim as optim

df = pd.read_csv('mldata_0003195463/mldata_0003195463.csv', index_col=0)
df

df_data_points = df.iloc[:, 1:]
df_data_points

df_data_points.shape # as pointed out in the instructions the dataset (excluded labels) is made of 25 features and 1400 data points

(1400, 25)

df_labels = df.iloc[:, 0]
df_labels

0       0
1       1
2       0
3       0
4       3
       ..
1395    4
1396    3
1397    0
1398    3
1399    4
Name: label, Length: 1400, dtype: int64

df_data_points_tr = df_data_points.T
df_data_points_tr

labels_t = df_labels.T
labels_t

0       0
1       1
2       0
3       0
4       3
       ..
1395    4
1396    3
1397    0
1398    3
1399    4
Name: label, Length: 1400, dtype: int64

print("Data Types:\n", df_data_points.dtypes)

Data Types:
 feature_1     float64
feature_2     float64
feature_3     float64
feature_4     float64
feature_5     float64
feature_6     float64
feature_7     float64
feature_8     float64
feature_9     float64
feature_10    float64
feature_11    float64
feature_12    float64
feature_13    float64
feature_14    float64
feature_15    float64
feature_16    float64
feature_17    float64
feature_18    float64
feature_19    float64
feature_20    float64
feature_21    float64
feature_22    float64
feature_23    float64
feature_24    float64
feature_25    float64
dtype: object

print("Features with Nan values:\n", df_data_points.isna().any())

Features with Nan values:
 feature_1     False
feature_2     False
feature_3     False
feature_4     False
feature_5     False
feature_6     False
feature_7     False
feature_8     False
feature_9     False
feature_10    False
feature_11    False
feature_12    False
feature_13    False
feature_14    False
feature_15    False
feature_16    False
feature_17    False
feature_18    False
feature_19    False
feature_20    False
feature_21    False
feature_22    False
feature_23    False
feature_24    False
feature_25    False
dtype: bool

df_data_points_tr_summary = df_data_points_tr.describe()
df_data_points_tr_summary

sns.displot(df_data_points_tr_summary.iloc[1], bins=50, color='green')
plt.title("distribution of mean of data points")
plt.show()

sns.displot(df_data_points_tr_summary.iloc[2], bins=50, color='blue')
plt.title("distribution of std of data points")
plt.show()

sns.displot(df_data_points_tr_summary.iloc[6], bins=50, color='red')
plt.title("distribution of mean of data points")
plt.show()

df_data_points_summary = df_data_points.describe()
df_data_points_summary

df_data_points.hist(figsize=(10, 15), bins=30, color='blue')
plt.show()

#plt.figure(figsize=(20, 15))  
corr = df_data_points.corr()
sns.heatmap(corr, 
            xticklabels=corr.columns.values,
            yticklabels=corr.columns.values)  
plt.show()

# Skeweness of the data points
col_points = list(df_data_points_tr.columns)
colP = np.shape(df_data_points_tr)[1]
df_skew_c = []
for i in range(colP):
    v_df = df_data_points_tr[col_points[i]]
    df_skew_c += [skew(v_df)]
df_skew_c
sns.histplot(df_skew_c, bins=100, color='blue', kde=True)
plt.xlabel('Skeweness of data points')
plt.show()

# Skeweness of the features
col_points = list(df_data_points.columns)
colP = np.shape(df_data_points)[1]
df_skew_c = []
for i in range(colP):
    v_df = df_data_points[col_points[i]]
    df_skew_c += [skew(v_df)]
print(len(df_skew_c))
sns.histplot(df_skew_c, bins=100, color='orange')
plt.xlabel('Skeweness of features')
plt.show()

25

# Kurtosis of data points
col_points = list(df_data_points_tr.columns)
colP = np.shape(df_data_points_tr)[1]
df_kurt_c = []
for i in range(colP):
    v_df = df_data_points_tr[col_points[i]]
    df_kurt_c += [kurtosis(v_df)]
df_kurt_c
sns.histplot(df_kurt_c, bins=100, color='purple', kde=True)
plt.xlabel('Kurtosis of data points')
plt.show()

# Kurtosis of features
col_points = list(df_data_points.columns)
colP = np.shape(df_data_points)[1]
df_kurt_c = []
for i in range(colP):
    v_df = df_data_points[col_points[i]]
    df_kurt_c += [kurtosis(v_df)]
print(len(df_kurt_c))
sns.histplot(df_kurt_c, bins=100, color='purple')
plt.xlabel('Kurtosis of data points')
plt.show()

25

print(labels_t.value_counts())
labels_t.value_counts().plot.pie(autopct='%.2f')

label
0    295
4    290
1    274
3    271
2    270
Name: count, dtype: int64

<Axes: ylabel='count'>

pca = PCA()
df_pca = pca.fit_transform(df_data_points)

cumulative_sum = np.cumsum(pca.explained_variance_ratio_)
plt.figure(figsize=(10, 4))

# plot 1
plt.subplot(1, 2, 1)
plt.title("Cumulative Variance")
plt.plot(cumulative_sum)
plt.xlabel("Component")
plt.ylabel("Explained Variance (%)")
plt.grid(True)
# plot 2
plt.subplot(1, 2, 2)
plt.title("Explained Variance per Component")
plt.plot(pca.explained_variance_ratio_)
plt.ylabel("Explained Variance (%)")
plt.xlabel('Component')
plt.grid(True)
plt.tight_layout()
plt.show()

# Plot 2D and 3D visualizations
labels = df["label"]
fig = plt.figure(figsize=(14, 7))

# 2D Plot
ax_2d = fig.add_subplot(121)
scatter_2d = ax_2d.scatter(df_pca[:, 0], df_pca[:, 1], c=labels)
ax_2d.set_xlabel("PCA1")
ax_2d.set_ylabel("PCA2")
ax_2d.set_title(f"Explained Variance: {round(pca.explained_variance_ratio_[0] + pca.explained_variance_ratio_[1], 2)}")

# 3D Plot
ax_3d = fig.add_subplot(122, projection='3d')
scatter_3d = ax_3d.scatter(df_pca[:, 0], df_pca[:, 1], df_pca[:, 2], c=labels)
ax_3d.set_xlabel("PCA1")
ax_3d.set_ylabel("PCA2")
ax_3d.set_zlabel("PCA3")
ax_3d.set_title(f"Explained Variance: {round(pca.explained_variance_ratio_[0] + pca.explained_variance_ratio_[1] + pca.explained_variance_ratio_[2], 2)}")

# Add legend
handles, legend_labels = scatter_2d.legend_elements()
ax_3d.legend(handles, legend_labels, loc='best', title='Classes')

plt.suptitle("PCA Visualization")
plt.tight_layout()
plt.show()

print(df_data_points.shape, df_labels.shape)
X_train, X_test, y_train, y_test = train_test_split(df_data_points, df_labels, test_size=0.2, random_state=42)
print(X_train.shape, y_train.shape)
print(X_test.shape, y_test.shape )

(1400, 25) (1400,)
(1120, 25) (1120,)
(280, 25) (280,)

rfc= RandomForestClassifier(random_state=42, n_jobs=-1,
                                       n_estimators=100)

rfc.fit(X_train,y_train)

RandomForestClassifier(n_jobs=-1, random_state=42)

RandomForestClassifier(n_jobs=-1, random_state=42)

y_pred = rfc.predict(X_test)

accuracy_score(y_pred, y_test)

0.6642857142857143

rf = RandomForestClassifier(n_jobs=-1, random_state=42)

parameters = {
    'max_depth': [10, 20, None],
    'criterion': ['gini', 'entropy'],
    'n_estimators': [1000, 1200, 1400]
    
}

grid_search = GridSearchCV(estimator=rf,
                           param_grid=parameters,
                           cv = 5,
                           n_jobs = -1, verbose=1,
                           scoring='accuracy')

grid_search.fit(X_train, y_train)

Fitting 5 folds for each of 18 candidates, totalling 90 fits

GridSearchCV(cv=5, estimator=RandomForestClassifier(n_jobs=-1, random_state=42),
             n_jobs=-1,
             param_grid={'criterion': ['gini', 'entropy'],
                         'max_depth': [10, 20, None],
                         'n_estimators': [1000, 1200, 1400]},
             scoring='accuracy', verbose=1)

GridSearchCV(cv=5, estimator=RandomForestClassifier(n_jobs=-1, random_state=42),
             n_jobs=-1,
             param_grid={'criterion': ['gini', 'entropy'],
                         'max_depth': [10, 20, None],
                         'n_estimators': [1000, 1200, 1400]},
             scoring='accuracy', verbose=1)

RandomForestClassifier(n_jobs=-1, random_state=42)

RandomForestClassifier(n_jobs=-1, random_state=42)

rf_best = grid_search.best_estimator_
rf_best

RandomForestClassifier(criterion='entropy', max_depth=20, n_estimators=1000,
                       n_jobs=-1, random_state=42)

RandomForestClassifier(criterion='entropy', max_depth=20, n_estimators=1000,
                       n_jobs=-1, random_state=42)

y_pred_grid = rf_best.predict(X_test)

accuracy_score(y_pred_grid, y_test)

0.7142857142857143

cf_matrix_rf_grid = confusion_matrix(y_test, y_pred_grid)
cf_matrix_rf_grid

array([[50,  4,  3,  3,  5],
       [ 4, 40,  2,  5,  1],
       [ 9,  1, 37,  5,  3],
       [ 8,  5,  0, 40,  3],
       [ 4,  5,  8,  2, 33]])

#plt.figure(figsize=(10, 7))
plt.imshow(cf_matrix_rf_grid, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for Random Forest with Grid Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_rf_grid.max() / 2.
for i, j in itertools.product(range(cf_matrix_rf_grid.shape[0]), range(cf_matrix_rf_grid.shape[1])):
    plt.text(j, i, cf_matrix_rf_grid[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_rf_grid[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

# number of trees in the random forest
n_estimators = [int(x) for x in np.linspace(start=200, stop=2000, num=10)]

# number of features to consider at every split
max_features = ['auto', 'sqrt', 'log2']

# depth at which stops

#max_depth = [None, 10, 20, 30]

# minimum number of samples required to split a node
min_samples_split = [2, 5, 10]

# minimum number of samples required at each leaf node
min_samples_leaf = [1, 2, 4, 10]

# Method of selecting samples for training each tree
bootstrap = [True, False]

# Random Grid
random_grid = {'n_estimators': n_estimators,
               'max_features': max_features,
               'criterion': ['gini', 'entropy'],
               #'max_depth': max_depth,
               'min_samples_split': min_samples_split,
               'min_samples_leaf': min_samples_leaf,
               'bootstrap': bootstrap}

print(random_grid)

{'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000], 'max_features': ['auto', 'sqrt', 'log2'], 'criterion': ['gini', 'entropy'], 'min_samples_split': [2, 5, 10], 'min_samples_leaf': [1, 2, 4, 10], 'bootstrap': [True, False]}

# I use the random grid now to search for the best hyperparameters
rf_rgrid = RandomForestClassifier()

# Random search of parameters, using 3 fold cross validation, 
# search across 100 different combinations, and use all available cores
rf_random = RandomizedSearchCV(estimator = rf_rgrid, param_distributions = random_grid, n_iter = 500, cv = 3, verbose=2, random_state=12, n_jobs = -1)

# Finally  I fit the random search model
rf_random.fit(X_train, y_train)

Fitting 3 folds for each of 500 candidates, totalling 1500 fits

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=False, criterion=gini, max_features=log2, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   2.0s
[CV] END bootstrap=False, criterion=gini, max_features=log2, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   2.1s
[CV] END bootstrap=False, criterion=gini, max_features=log2, min_samples_leaf=1, min_samples_split=10, n_estimators=600; total time=   2.1s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=False, criterion=gini, max_features=sqrt, min_samples_leaf=10, min_samples_split=2, n_estimators=1400; total time=   4.1s
[CV] END bootstrap=False, criterion=gini, max_features=sqrt, min_samples_leaf=10, min_samples_split=2, n_estimators=1400; total time=   4.2s
[CV] END bootstrap=False, criterion=gini, max_features=sqrt, min_samples_leaf=10, min_samples_split=2, n_estimators=1400; total time=   4.4s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=True, criterion=entropy, max_features=log2, min_samples_leaf=1, min_samples_split=5, n_estimators=600; total time=   2.4s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=True, criterion=gini, max_features=auto, min_samples_leaf=2, min_samples_split=2, n_estimators=2000; total time=   6.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

rf_random.best_params_

{'n_estimators': 1200,
 'min_samples_split': 2,
 'min_samples_leaf': 1,
 'max_features': 'log2',
 'criterion': 'gini',
 'bootstrap': False}

best_random_est = rf_random.best_estimator_
best_random_est

RandomForestClassifier(bootstrap=False, max_features='log2', n_estimators=1200)

RandomForestClassifier(bootstrap=False, max_features='log2', n_estimators=1200)

best_random_est.fit(X_train, y_train)

RandomForestClassifier(bootstrap=False, max_features='log2', n_estimators=1200)

RandomForestClassifier(bootstrap=False, max_features='log2', n_estimators=1200)

y_pred_g_random = best_random_est.predict(X_test)

accuracy_score(y_pred_g_random, y_test)

0.7285714285714285

cf_matrix_rf_random = confusion_matrix(y_test, y_pred_g_random)
cf_matrix_rf_random

array([[51,  4,  3,  2,  5],
       [ 2, 40,  2,  6,  2],
       [ 5,  1, 40,  3,  6],
       [ 8,  4,  0, 40,  4],
       [ 3,  5,  7,  2, 35]])

plt.imshow(cf_matrix_rf_random, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for Random Forest with Random Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_rf_random.max() / 2.
for i, j in itertools.product(range(cf_matrix_rf_random.shape[0]), range(cf_matrix_rf_random.shape[1])):
    plt.text(j, i, cf_matrix_rf_random[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_rf_random[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

# Define the search space
search_space = {
    'n_estimators': Integer(200, 2000),
    'max_features': Categorical(['auto', 'sqrt', 'log2']),
    'max_depth': Integer(10, 110),
    'min_samples_split': Integer(2, 10),
    'min_samples_leaf': Integer(1, 10),
    'bootstrap': Categorical([True, False])
}

# Initialize the model
rf_b = RandomForestClassifier(random_state=42)

# Bayesian search
bayes_search = BayesSearchCV(
    estimator=rf_b,
    search_spaces=search_space,
    n_iter=100,
    cv=3,
    n_jobs=-1,
    verbose=2,
    random_state=42
)

# Fit the Bayesian search
bayes_search.fit(X_train, y_train)

Fitting 3 folds for each of 1 candidates, totalling 3 fits

[CV] END bootstrap=True, max_depth=83, max_features=log2, min_samples_leaf=4, min_samples_split=7, n_estimators=945; total time=   1.8s
[CV] END bootstrap=True, max_depth=83, max_features=log2, min_samples_leaf=4, min_samples_split=7, n_estimators=945; total time=   1.8s
[CV] END bootstrap=True, max_depth=83, max_features=log2, min_samples_leaf=4, min_samples_split=7, n_estimators=945; total time=   1.8s
Fitting 3 folds for each of 1 candidates, totalling 3 fits

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=False, max_depth=98, max_features=auto, min_samples_leaf=10, min_samples_split=9, n_estimators=312; total time=   0.8s
[CV] END bootstrap=False, max_depth=98, max_features=auto, min_samples_leaf=10, min_samples_split=9, n_estimators=312; total time=   0.8s
[CV] END bootstrap=False, max_depth=98, max_features=auto, min_samples_leaf=10, min_samples_split=9, n_estimators=312; total time=   0.8s
Fitting 3 folds for each of 1 candidates, totalling 3 fits

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=True, max_depth=102, max_features=auto, min_samples_leaf=5, min_samples_split=4, n_estimators=1017; total time=   2.1s
[CV] END bootstrap=True, max_depth=102, max_features=auto, min_samples_leaf=5, min_samples_split=4, n_estimators=1017; total time=   2.2s
[CV] END bootstrap=True, max_depth=102, max_features=auto, min_samples_leaf=5, min_samples_split=4, n_estimators=1017; total time=   2.1s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=27, max_features=sqrt, min_samples_leaf=8, min_samples_split=6, n_estimators=372; total time=   1.0s
[CV] END bootstrap=False, max_depth=27, max_features=sqrt, min_samples_leaf=8, min_samples_split=6, n_estimators=372; total time=   1.0s
[CV] END bootstrap=False, max_depth=27, max_features=sqrt, min_samples_leaf=8, min_samples_split=6, n_estimators=372; total time=   0.9s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=54, max_features=sqrt, min_samples_leaf=7, min_samples_split=9, n_estimators=1491; total time=   3.9s
[CV] END bootstrap=False, max_depth=54, max_features=sqrt, min_samples_leaf=7, min_samples_split=9, n_estimators=1491; total time=   3.9s
[CV] END bootstrap=False, max_depth=54, max_features=sqrt, min_samples_leaf=7, min_samples_split=9, n_estimators=1491; total time=   4.0s
Fitting 3 folds for each of 1 candidates, totalling 3 fits

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=False, max_depth=104, max_features=auto, min_samples_leaf=3, min_samples_split=8, n_estimators=871; total time=   2.6s
[CV] END bootstrap=False, max_depth=104, max_features=auto, min_samples_leaf=3, min_samples_split=8, n_estimators=871; total time=   2.6s
[CV] END bootstrap=False, max_depth=104, max_features=auto, min_samples_leaf=3, min_samples_split=8, n_estimators=871; total time=   2.6s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=88, max_features=sqrt, min_samples_leaf=9, min_samples_split=7, n_estimators=1270; total time=   3.2s
[CV] END bootstrap=False, max_depth=88, max_features=sqrt, min_samples_leaf=9, min_samples_split=7, n_estimators=1270; total time=   3.2s
[CV] END bootstrap=False, max_depth=88, max_features=sqrt, min_samples_leaf=9, min_samples_split=7, n_estimators=1270; total time=   3.2s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=9, min_samples_split=5, n_estimators=292; total time=   0.7s
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=9, min_samples_split=5, n_estimators=292; total time=   0.7s
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=9, min_samples_split=5, n_estimators=292; total time=   0.7s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=80, max_features=log2, min_samples_leaf=5, min_samples_split=5, n_estimators=581; total time=   1.4s
[CV] END bootstrap=False, max_depth=80, max_features=log2, min_samples_leaf=5, min_samples_split=5, n_estimators=581; total time=   1.4s
[CV] END bootstrap=False, max_depth=80, max_features=log2, min_samples_leaf=5, min_samples_split=5, n_estimators=581; total time=   1.4s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=True, max_depth=92, max_features=log2, min_samples_leaf=3, min_samples_split=7, n_estimators=694; total time=   1.4s
[CV] END bootstrap=True, max_depth=92, max_features=log2, min_samples_leaf=3, min_samples_split=7, n_estimators=694; total time=   1.4s
[CV] END bootstrap=True, max_depth=92, max_features=log2, min_samples_leaf=3, min_samples_split=7, n_estimators=694; total time=   1.4s
Fitting 3 folds for each of 1 candidates, totalling 3 fits

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(
/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/ensemble/_forest.py:424: FutureWarning: `max_features='auto'` has been deprecated in 1.1 and will be removed in 1.3. To keep the past behaviour, explicitly set `max_features='sqrt'` or remove this parameter as it is also the default value for RandomForestClassifiers and ExtraTreesClassifiers.
  warn(

[CV] END bootstrap=False, max_depth=105, max_features=auto, min_samples_leaf=1, min_samples_split=9, n_estimators=200; total time=   0.6s
[CV] END bootstrap=False, max_depth=105, max_features=auto, min_samples_leaf=1, min_samples_split=9, n_estimators=200; total time=   0.6s
[CV] END bootstrap=False, max_depth=105, max_features=auto, min_samples_leaf=1, min_samples_split=9, n_estimators=200; total time=   0.6s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=True, max_depth=64, max_features=log2, min_samples_leaf=2, min_samples_split=8, n_estimators=2000; total time=   4.0s
[CV] END bootstrap=True, max_depth=64, max_features=log2, min_samples_leaf=2, min_samples_split=8, n_estimators=2000; total time=   4.0s
[CV] END bootstrap=True, max_depth=64, max_features=log2, min_samples_leaf=2, min_samples_split=8, n_estimators=2000; total time=   4.0s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=53, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=200; total time=   0.6s
[CV] END bootstrap=False, max_depth=53, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=200; total time=   0.6s
[CV] END bootstrap=False, max_depth=53, max_features=sqrt, min_samples_leaf=2, min_samples_split=3, n_estimators=200; total time=   0.6s
Fitting 3 folds for each of 1 candidates, totalling 3 fits
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=1983; total time=   6.6s
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=1983; total time=   6.6s
[CV] END bootstrap=False, max_depth=102, max_features=sqrt, min_samples_leaf=1, min_samples_split=3, n_estimators=1983; total time=   6.7s
Fitting 3 folds for each of 1 candidates, totalling 3 fits

# Best parameters and accuracy
print(f"Best parameters: {bayes_search.best_params_}")
print(f"Best cross-validation accuracy: {bayes_search.best_score_}")

Best parameters: OrderedDict([('bootstrap', False), ('max_depth', 78), ('max_features', 'log2'), ('min_samples_leaf', 1), ('min_samples_split', 2), ('n_estimators', 326)])
Best cross-validation accuracy: 0.6839424046489179

# Evaluate on the test set
best_rf_bayes = bayes_search.best_estimator_
#test_accuracy_bayes = best_rf_bayes.score(X_test, y_test)
#print(f"Test accuracy: {test_accuracy_bayes:.4f}")

best_rf_bayes

RandomForestClassifier(bootstrap=False, max_depth=78, max_features='log2',
                       n_estimators=326, random_state=42)

RandomForestClassifier(bootstrap=False, max_depth=78, max_features='log2',
                       n_estimators=326, random_state=42)

y_pred_bayes = best_rf_bayes.predict(X_test)

accuracy_score(y_pred_bayes, y_test)

0.7321428571428571

cf_matrix_rf_bayes = confusion_matrix(y_test, y_pred_bayes)
cf_matrix_rf_bayes

array([[51,  5,  3,  2,  4],
       [ 2, 39,  2,  7,  2],
       [ 6,  1, 42,  1,  5],
       [ 8,  6,  0, 38,  4],
       [ 4,  5,  7,  1, 35]])

plt.imshow(cf_matrix_rf_bayes, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for Random Forest with Bayes Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_rf_bayes.max() / 2.
for i, j in itertools.product(range(cf_matrix_rf_bayes.shape[0]), range(cf_matrix_rf_bayes.shape[1])):
    plt.text(j, i, cf_matrix_rf_bayes[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_rf_bayes[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

from sklearn.tree import plot_tree
fig = plt.figure(figsize=(8,8))
plt.figure(figsize=(80,40))
plot_tree(best_rf_bayes.estimators_[0], feature_names=df_data_points.columns, class_names=['0', '1', '2', '3', '4'], filled=True)
fig.savefig('rf_individualtree.png')

<Figure size 800x800 with 0 Axes>

df_importance = pd.DataFrame(best_rf_bayes.feature_importances_, index=df_data_points.columns, columns=['importance'])
df_importance_sorted = df_importance.sort_values(by='importance', ascending=False)
df_importance_sorted

average_method ='macro'
for score in (precision_score, recall_score, f1_score):
    sgrid_stat_rf = score(y_test, y_pred_grid, average=average_method)
    srandom_stat_rf = score(y_test, y_pred_g_random, average=average_method)
    sbayes_stat_rf = score(y_test, y_pred_bayes, average=average_method)
    print(score.__name__, (sgrid_stat_rf, srandom_stat_rf, sbayes_stat_rf))

precision_score (0.7189090909090909, 0.7289155811508753, 0.7336052824885823)
recall_score (0.712017982017982, 0.7256543456543457, 0.72998001998002)
f1_score (0.7135688524608459, 0.7262796461786843, 0.730589691534106)

c_report_grid_rf = classification_report(y_test, y_pred_grid, target_names=['0', '1', '2', '3', '4'])
c_report_random_rf = classification_report(y_test, y_pred_g_random, target_names=['0', '1', '2', '3', '4'])
c_report_bayes_rf = classification_report(y_test, y_pred_bayes, target_names=['0', '1', '2', '3', '4'])
print(c_report_grid_rf, c_report_random_rf, c_report_bayes_rf)

              precision    recall  f1-score   support

           0       0.67      0.77      0.71        65
           1       0.73      0.77      0.75        52
           2       0.74      0.67      0.70        55
           3       0.73      0.71      0.72        56
           4       0.73      0.63      0.68        52

    accuracy                           0.71       280
   macro avg       0.72      0.71      0.71       280
weighted avg       0.72      0.71      0.71       280
               precision    recall  f1-score   support

           0       0.72      0.80      0.76        65
           1       0.73      0.77      0.75        52
           2       0.73      0.69      0.71        55
           3       0.78      0.71      0.75        56
           4       0.68      0.65      0.67        52

    accuracy                           0.73       280
   macro avg       0.73      0.73      0.73       280
weighted avg       0.73      0.73      0.73       280
               precision    recall  f1-score   support

           0       0.72      0.78      0.75        65
           1       0.70      0.75      0.72        52
           2       0.78      0.76      0.77        55
           3       0.78      0.68      0.72        56
           4       0.70      0.67      0.69        52

    accuracy                           0.73       280
   macro avg       0.73      0.73      0.73       280
weighted avg       0.73      0.73      0.73       280

knn = KNeighborsClassifier()
knn.fit(X_train, y_train)

KNeighborsClassifier()

KNeighborsClassifier()

y_pred_knn = knn.predict(X_test)
accuracy_score(y_pred_knn, y_test)

0.6785714285714286

accuracy = []
k_values = list(range(1, 100, 2))

for k in k_values:
    knn = KNeighborsClassifier(n_neighbors=k)
    knn.fit(X_train, y_train)
    y_pred = knn.predict(X_test)
    accuracy.append(accuracy_score(y_pred, y_test))

# Find the k value with maximum accuracy
max_accuracy_index = np.argmax(accuracy)
k_max_accuracy = k_values[max_accuracy_index]
print(f"The number of neighbors where the accuracy is maximized is: {k_max_accuracy}")


# First plot
plt.figure(figsize=(10, 6))  # Adjust size as needed
plt.subplot(2, 1, 1)  # 2 rows, 1 column, first plot
plt.xlabel('Number of Neighbours')
plt.ylabel('Accuracy')
plt.plot(range(1, 100, 2), accuracy, color='blue', linestyle='dashed', marker='o', markerfacecolor='red', markersize=10)

# Second plot
plt.subplot(2, 1, 2)  # 2 rows, 1 column, second plot
plt.bar([i for i in range(1, len(accuracy)*2, 2)], accuracy)  # Adjust range to match length of accuracy
plt.xlabel('Number of Neighbours')
plt.ylabel('Accuracy')

plt.tight_layout()  # Adjusts subplot params so that subplots are nicely fit in the figure.
plt.show()

The number of neighbors where the accuracy is maximized is: 9

accuracy = []
k_values = list(range(1, 100, 2))

for k in k_values:
    knn = KNeighborsClassifier(n_neighbors=k)
    scores = cross_val_score(knn, df_data_points, df_labels, cv=5, scoring='accuracy')
    accuracy.append(scores.mean())

# Find the k value with maximum accuracy
max_accuracy_index = np.argmax(accuracy)
k_max_accuracy = k_values[max_accuracy_index]
print(f"The number of neighbors where the accuracy is maximized is: {k_max_accuracy}")


# First plot
plt.figure(figsize=(10, 6))  # Adjust size as needed
plt.subplot(2, 1, 1)  # 2 rows, 1 column, first plot
plt.xlabel('Number of Neighbours')
plt.ylabel('Accuracy')
plt.plot(range(1, 100, 2), accuracy, color='blue', linestyle='dashed', marker='o', markerfacecolor='red', markersize=10)

# Second plot
plt.subplot(2, 1, 2)  # 2 rows, 1 column, second plot
plt.bar([i for i in range(1, len(accuracy)*2, 2)], accuracy)  # Adjust range to match length of accuracy
plt.xlabel('Number of Neighbours')
plt.ylabel('Accuracy')

plt.tight_layout()  # Adjusts subplot params so that subplots are nicely fit in the figure.
plt.show()

The number of neighbors where the accuracy is maximized is: 9

# Define the parameter grid
param_grid_k = {
    'n_neighbors': list(range(1, 20, 2)),
    'weights': ['uniform', 'distance'],
    'metric': ['euclidean', 'manhattan', 'minkowski', 'chebyshev'],
    'algorithm': ['auto', 'ball_tree', 'kd_tree']
    
}

# Initialize the KNN classifier
knn_g = KNeighborsClassifier()

# Initialize GridSearchCV
grid_search_knn = GridSearchCV(estimator=knn_g, param_grid=param_grid_k, cv=5, n_jobs=-1, verbose=2, scoring='accuracy')

# Fit GridSearchCV
grid_search_knn.fit(X_train, y_train)

# Best parameters and accuracy
print(f"Best parameters: {grid_search_knn.best_params_}")
print(f"Best cross-validation accuracy: {grid_search_knn.best_score_}")

Fitting 5 folds for each of 240 candidates, totalling 1200 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.1s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s

[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s

[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s

[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s

[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s

[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s

[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s

[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s

[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s

[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.1s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s

[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
Best parameters: {'algorithm': 'auto', 'metric': 'manhattan', 'n_neighbors': 9, 'weights': 'distance'}
Best cross-validation accuracy: 0.6776785714285716

best_knn_grid = grid_search_knn.best_estimator_
best_knn_grid

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

# Evaluate on the test set with the best estimator

y_pred_best_k_grid = best_knn_grid.predict(X_test)
best_accuracy = accuracy_score(y_test, y_pred_best_k_grid)
print(f'Best KNN Test Accuracy: {best_accuracy:.4f}')

Best KNN Test Accuracy: 0.7071

cf_matrix_knn_grid = confusion_matrix(y_test, y_pred_best_k_grid)
cf_matrix_knn_grid

array([[50,  4,  3,  3,  5],
       [ 1, 43,  1,  3,  4],
       [10,  1, 36,  2,  6],
       [ 9, 10,  0, 34,  3],
       [ 4,  2,  8,  3, 35]])

#plt.figure(figsize=(10, 7))
plt.imshow(cf_matrix_knn_grid, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for KNN with Grid Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_knn_grid.max() / 2.
for i, j in itertools.product(range(cf_matrix_knn_grid.shape[0]), range(cf_matrix_knn_grid.shape[1])):
    plt.text(j, i, cf_matrix_knn_grid[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_knn_grid[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

param_dist_random = {
    'n_neighbors': list(range(1, 20, 2)),
    'weights': ['uniform', 'distance'],
    'metric': ['euclidean', 'manhattan', 'minkowski', 'chebyshev'],
    'algorithm': ['auto', 'ball_tree', 'kd_tree']
}

knn_random = KNeighborsClassifier()

# Initialize RandomizedSearchCV
random_search_knn = RandomizedSearchCV(estimator=knn_random, param_distributions=param_dist_random, n_iter=500, cv=5, n_jobs=-1, verbose=2, scoring='accuracy', random_state=42)

# Fit RandomizedSearchCV
random_search_knn.fit(X_train, y_train)

# Best parameters and accuracy
print(f"Best parameters: {random_search_knn.best_params_}")
print(f"Best cross-validation accuracy: {random_search_knn.best_score_}")

Fitting 5 folds for each of 240 candidates, totalling 1200 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/sklearn/model_selection/_search.py:305: UserWarning: The total space of parameters 240 is smaller than n_iter=500. Running 240 iterations. For exhaustive searches, use GridSearchCV.
  warnings.warn(

[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s[CV] END algorithm=auto, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s

[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s

[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s

[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s

[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s

[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s

[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s

[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s

[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s

[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=19, weights=distance; total time=   0.0s
Best parameters: {'weights': 'distance', 'n_neighbors': 9, 'metric': 'manhattan', 'algorithm': 'auto'}
Best cross-validation accuracy: 0.6776785714285716

best_knn_random = random_search_knn.best_estimator_
best_knn_random

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

# Evaluate on the test set with the best estimator
y_pred_best_random_knn = best_knn_random.predict(X_test)
best_accuracy_random_knn = accuracy_score(y_test, y_pred_best_random_knn)
print(f'Best KNN Test Accuracy (Random Search): {best_accuracy_random_knn:.4f}')

Best KNN Test Accuracy (Random Search): 0.7071

cf_matrix_knn_random = confusion_matrix(y_test, y_pred_best_random_knn)
cf_matrix_knn_random

array([[50,  4,  3,  3,  5],
       [ 1, 43,  1,  3,  4],
       [10,  1, 36,  2,  6],
       [ 9, 10,  0, 34,  3],
       [ 4,  2,  8,  3, 35]])

#plt.figure(figsize=(10, 7))
plt.imshow(cf_matrix_knn_random, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for KNN with Random Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_knn_random.max() / 2.
for i, j in itertools.product(range(cf_matrix_knn_random.shape[0]), range(cf_matrix_knn_random.shape[1])):
    plt.text(j, i, cf_matrix_knn_random[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_knn_random[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

search_space_k = {
    'n_neighbors': Integer(1, 20),
    'weights': Categorical(['uniform', 'distance']),
    'metric': Categorical(['euclidean', 'manhattan', 'minkowski', 'chebyshev']),
    'algorithm': Categorical(['auto', 'ball_tree', 'kd_tree'])
}

# Initialize the KNN classifier
knn_b = KNeighborsClassifier()

# Initialize BayesSearchCV
bayes_search = BayesSearchCV(
    estimator=knn_b,
    search_spaces=search_space_k,
    n_iter=100,  # Number of iterations
    cv=5,  # Number of cross-validation folds
    n_jobs=-1,
    verbose=2,
    random_state=42,
    scoring='accuracy'
)

# Fit BayesSearchCV
bayes_search.fit(X_train, y_train)

# Best parameters and accuracy
print(f"Best parameters: {bayes_search.best_params_}")
print(f"Best cross-validation accuracy: {bayes_search.best_score_}")

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=19, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=7, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=3, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=4, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=8, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=10, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=18, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=15, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=1, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=1, weights=distance; total time=   0.0s

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=13, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=6, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=17, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=14, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=1, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=12, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s[CV] END algorithm=auto, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s

[CV] END algorithm=auto, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=14, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=11, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=9, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=6, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=1, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=20, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=8, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=8, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=10, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=18, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=18, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=18, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=15, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=3, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=4, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=14, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=14, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=14, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=14, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=14, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=12, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=14, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=14, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=10, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=10, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=16, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=9, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=7, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=3, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=16, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=17, weights=uniform; total time=   0.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point ['ball_tree', 'manhattan', 9, 'distance'] before, using random point ['kd_tree', 'manhattan', 12, 'distance']
  warnings.warn(

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=4, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=4, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=4, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=12, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=19, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=1, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=5, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=7, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=17, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=10, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=18, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=18, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=euclidean, n_neighbors=15, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=17, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=chebyshev, n_neighbors=9, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=euclidean, n_neighbors=20, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=5, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=11, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=uniform; total time=   0.0s
[CV] END algorithm=kd_tree, metric=manhattan, n_neighbors=12, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=13, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=8, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=8, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=8, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=8, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=8, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=3, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=6, weights=uniform; total time=   0.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point ['ball_tree', 'manhattan', 9, 'distance'] before, using random point ['auto', 'minkowski', 10, 'uniform']
  warnings.warn(

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=10, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=10, weights=uniform; total time=   0.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point ['ball_tree', 'manhattan', 9, 'distance'] before, using random point ['ball_tree', 'euclidean', 2, 'distance']
  warnings.warn(

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=2, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=2, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=2, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=2, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=euclidean, n_neighbors=2, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=16, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=16, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=16, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=16, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=16, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=manhattan, n_neighbors=19, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=minkowski, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=6, weights=distance; total time=   0.0s
[CV] END algorithm=auto, metric=minkowski, n_neighbors=6, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=4, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=minkowski, n_neighbors=4, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=5, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=6, weights=uniform; total time=   0.0s
[CV] END algorithm=ball_tree, metric=chebyshev, n_neighbors=6, weights=uniform; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s
[CV] END algorithm=auto, metric=manhattan, n_neighbors=13, weights=uniform; total time=   0.0s

/Users/federicopezzoli/opt/anaconda3/lib/python3.9/site-packages/skopt/optimizer/optimizer.py:517: UserWarning: The objective has been evaluated at point ['ball_tree', 'manhattan', 9, 'distance'] before, using random point ['kd_tree', 'minkowski', 13, 'distance']
  warnings.warn(

Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=minkowski, n_neighbors=13, weights=distance; total time=   0.0s
Fitting 5 folds for each of 1 candidates, totalling 5 fits
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=16, weights=distance; total time=   0.0s
[CV] END algorithm=kd_tree, metric=chebyshev, n_neighbors=16, weights=distance; total time=   0.0s

best_knn_bayes = bayes_search.best_estimator_
best_knn_bayes

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

KNeighborsClassifier(metric='manhattan', n_neighbors=9, weights='distance')

y_pred_best_bayes_knn = best_knn_bayes.predict(X_test)
best_accuracy_bayes_knn = accuracy_score(y_test, y_pred_best_bayes_knn)
print(f'Best KNN Test Accuracy (Bayesian Search): {best_accuracy_bayes_knn:.4f}')

Best KNN Test Accuracy (Bayesian Search): 0.7071

cf_matrix_knn_bayes = confusion_matrix(y_test, y_pred_best_bayes_knn)
cf_matrix_knn_bayes

array([[50,  4,  3,  3,  5],
       [ 1, 43,  1,  3,  4],
       [10,  1, 36,  2,  6],
       [ 9, 10,  0, 34,  3],
       [ 4,  2,  8,  3, 35]])

#plt.figure(figsize=(10, 7))
plt.imshow(cf_matrix_knn_bayes, interpolation='nearest', cmap='Blues')
plt.title('Confusion Matrix for KNN with Bayes Search')
plt.colorbar()

# Draw the grid boxes
class_names = ['0', '1', '2', '3', '4']
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names)
plt.yticks(tick_marks, class_names)

# Draw the text boxes
thresh = cf_matrix_knn_bayes.max() / 2.
for i, j in itertools.product(range(cf_matrix_knn_bayes.shape[0]), range(cf_matrix_knn_bayes.shape[1])):
    plt.text(j, i, cf_matrix_knn_bayes[i, j],
             horizontalalignment="center",
             color="white" if cf_matrix_knn_bayes[i, j] > thresh else "black")

plt.tight_layout()
plt.ylabel('Actual label')
plt.xlabel('Predicted label')
plt.show()

average_method ='macro'
for score in (precision_score, recall_score, f1_score):
    sgrid_stat_knn = score(y_test, y_pred_best_k_grid, average=average_method)
    srandom_stat_knn = score(y_test, y_pred_best_random_knn, average=average_method)
    sbayes_stat_knn = score(y_test, y_pred_best_bayes_knn, average=average_method)
    print(score.__name__, (sgrid_stat_knn, srandom_stat_knn, sbayes_stat_knn))

precision_score (0.7116550512776928, 0.7116550512776928, 0.7116550512776928)
recall_score (0.7061838161838162, 0.7061838161838162, 0.7061838161838162)
f1_score (0.7052489445803459, 0.7052489445803459, 0.7052489445803459)

c_report_grid_knn = classification_report(y_test, y_pred_best_k_grid, target_names=['0', '1', '2', '3', '4'])
c_report_random_knn = classification_report(y_test, y_pred_best_random_knn, target_names=['0', '1', '2', '3', '4'])
c_report_bayes_knn = classification_report(y_test, y_pred_best_bayes_knn, target_names=['0', '1', '2', '3', '4'])
print(c_report_grid_knn, c_report_random_knn, c_report_bayes_knn)

              precision    recall  f1-score   support

           0       0.68      0.77      0.72        65
           1       0.72      0.83      0.77        52
           2       0.75      0.65      0.70        55
           3       0.76      0.61      0.67        56
           4       0.66      0.67      0.67        52

    accuracy                           0.71       280
   macro avg       0.71      0.71      0.71       280
weighted avg       0.71      0.71      0.71       280
               precision    recall  f1-score   support

           0       0.68      0.77      0.72        65
           1       0.72      0.83      0.77        52
           2       0.75      0.65      0.70        55
           3       0.76      0.61      0.67        56
           4       0.66      0.67      0.67        52

    accuracy                           0.71       280
   macro avg       0.71      0.71      0.71       280
weighted avg       0.71      0.71      0.71       280
               precision    recall  f1-score   support

           0       0.68      0.77      0.72        65
           1       0.72      0.83      0.77        52
           2       0.75      0.65      0.70        55
           3       0.76      0.61      0.67        56
           4       0.66      0.67      0.67        52

    accuracy                           0.71       280
   macro avg       0.71      0.71      0.71       280
weighted avg       0.71      0.71      0.71       280

average_method ='macro'
for score in (precision_score, recall_score, f1_score):
    rf_final = score(y_test, y_pred_bayes, average=average_method)
    knn_final = score(y_test, y_pred_best_k_grid, average=average_method)
    print(score.__name__, (rf_final, knn_final))

precision_score (0.7336052824885823, 0.7116550512776928)
recall_score (0.72998001998002, 0.7061838161838162)
f1_score (0.730589691534106, 0.7052489445803459)

c_report_rf_final = classification_report(y_test, y_pred_bayes, target_names=['0', '1', '2', '3', '4'])
c_report_knn_final = classification_report(y_test, y_pred_best_k_grid, target_names=['0', '1', '2', '3', '4'])
print(c_report_rf_final, c_report_knn_final)

              precision    recall  f1-score   support

           0       0.72      0.78      0.75        65
           1       0.70      0.75      0.72        52
           2       0.78      0.76      0.77        55
           3       0.78      0.68      0.72        56
           4       0.70      0.67      0.69        52

    accuracy                           0.73       280
   macro avg       0.73      0.73      0.73       280
weighted avg       0.73      0.73      0.73       280
               precision    recall  f1-score   support

           0       0.68      0.77      0.72        65
           1       0.72      0.83      0.77        52
           2       0.75      0.65      0.70        55
           3       0.76      0.61      0.67        56
           4       0.66      0.67      0.67        52

    accuracy                           0.71       280
   macro avg       0.71      0.71      0.71       280
weighted avg       0.71      0.71      0.71       280

class NeuralNetwork(nn.Module):
    def __init__(self):
        super(NeuralNetwork, self).__init__()
        self.model = nn.Sequential(
            nn.Flatten(),
            nn.Linear(25, 512),  # Input layer adjusted to 25 features
            nn.LeakyReLU(),
            nn.Dropout(0.4),
            
            nn.Linear(512, 256),  # Hidden layer
            nn.LeakyReLU(),
            nn.BatchNorm1d(256),
            nn.Dropout(0.4),
            
            nn.Linear(256, 128),  # Hidden layer
            nn.LeakyReLU(),
            nn.Dropout(0.3),
            
            nn.Linear(128, 64),  # Hidden layer
            nn.LeakyReLU(),
            
            nn.Linear(64, 5),  # Output layer adjusted to 5 classes
            nn.Softmax(dim=1)  # Softmax activation for multi-class classification
        )
    
    def forward(self, x):
        return self.model(x)

model_nn = NeuralNetwork()
print(model_nn)

NeuralNetwork(
  (model): Sequential(
    (0): Flatten(start_dim=1, end_dim=-1)
    (1): Linear(in_features=25, out_features=512, bias=True)
    (2): LeakyReLU(negative_slope=0.01)
    (3): Dropout(p=0.4, inplace=False)
    (4): Linear(in_features=512, out_features=256, bias=True)
    (5): LeakyReLU(negative_slope=0.01)
    (6): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (7): Dropout(p=0.4, inplace=False)
    (8): Linear(in_features=256, out_features=128, bias=True)
    (9): LeakyReLU(negative_slope=0.01)
    (10): Dropout(p=0.3, inplace=False)
    (11): Linear(in_features=128, out_features=64, bias=True)
    (12): LeakyReLU(negative_slope=0.01)
    (13): Linear(in_features=64, out_features=5, bias=True)
    (14): Softmax(dim=1)
  )
)

X_train_nn, X_val_nn, y_train_nn, y_val_nn = train_test_split(X_train.values, y_train.values, test_size=0.2, random_state=42)


X_train_tensor = torch.tensor(X_train_nn, dtype=torch.float32)
y_train_tensor = torch.tensor(y_train_nn, dtype=torch.long)
X_val_tensor = torch.tensor(X_val_nn, dtype=torch.float32)
y_val_tensor = torch.tensor(y_val_nn, dtype=torch.long)

import torch
import torch.nn as nn
import torch.optim as optim

# Assuming model_DS_H is your NeuralNetworkDropSeq model

# Use CrossEntropyLoss for multi-class classification
criterion = nn.CrossEntropyLoss() 

# Use an optimizer (SGD in this case)
optimizer = torch.optim.SGD(model_nn.parameters(), lr=0.01)

epochs = 10000
best_val_acc = 0
patience = 3
no_improve_epochs = 0

best_model_path_nn = 'best_model_final_nn.pth'

for epoch in range(epochs):
    model_nn.train()
    optimizer.zero_grad()  # Reset the gradients of all model parameters to zero.
    train_output = model_nn(X_train_tensor)  # Forward pass with all training data
    train_loss = criterion(train_output, y_train_tensor)  # Calculate the loss
    train_loss.backward()  # Compute the gradients of the loss with respect to the model's parameters
    optimizer.step()  # Update the weights
    
    # Calculate training accuracy
    with torch.no_grad():
        train_predictions = torch.argmax(train_output, dim=1)  # Get the predicted class indices
        train_correct = (train_predictions == y_train_tensor).sum().item()
        train_total = y_train_tensor.size(0)
        train_acc = train_correct / train_total

    # Validation
    model_nn.eval()  # Set the model to evaluation mode
    with torch.no_grad():
        val_output = model_nn(X_val_tensor)  # Compute predictions on the validation dataset
        val_loss = criterion(val_output, y_val_tensor)
        val_predictions = torch.argmax(val_output, dim=1)  # Get the predicted class indices
        val_correct = (val_predictions == y_val_tensor).sum().item()
        val_total = y_val_tensor.size(0)
        val_acc = val_correct / val_total

    print(f'Epoch {epoch+1}/{epochs}, '
          f'Train Loss: {train_loss.item():.4f}, '
          f'Train Accuracy: {train_acc:.4f}, '
          f'Val Loss: {val_loss.item():.4f}, '
          f'Val Accuracy: {val_acc:.4f}')

Epoch 1/10000, Train Loss: 1.6105, Train Accuracy: 0.1853, Val Loss: 1.6100, Val Accuracy: 0.1741
Epoch 2/10000, Train Loss: 1.6095, Train Accuracy: 0.1920, Val Loss: 1.6100, Val Accuracy: 0.1741
Epoch 3/10000, Train Loss: 1.6107, Train Accuracy: 0.1942, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 4/10000, Train Loss: 1.6112, Train Accuracy: 0.1853, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 5/10000, Train Loss: 1.6106, Train Accuracy: 0.1875, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 6/10000, Train Loss: 1.6101, Train Accuracy: 0.1897, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 7/10000, Train Loss: 1.6094, Train Accuracy: 0.1998, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 8/10000, Train Loss: 1.6092, Train Accuracy: 0.2009, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 9/10000, Train Loss: 1.6088, Train Accuracy: 0.2042, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 10/10000, Train Loss: 1.6112, Train Accuracy: 0.1864, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 11/10000, Train Loss: 1.6107, Train Accuracy: 0.2009, Val Loss: 1.6100, Val Accuracy: 0.1786
Epoch 12/10000, Train Loss: 1.6100, Train Accuracy: 0.2042, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 13/10000, Train Loss: 1.6098, Train Accuracy: 0.1886, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 14/10000, Train Loss: 1.6087, Train Accuracy: 0.2054, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 15/10000, Train Loss: 1.6105, Train Accuracy: 0.1920, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 16/10000, Train Loss: 1.6110, Train Accuracy: 0.1652, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 17/10000, Train Loss: 1.6098, Train Accuracy: 0.1998, Val Loss: 1.6099, Val Accuracy: 0.1786
Epoch 18/10000, Train Loss: 1.6108, Train Accuracy: 0.1730, Val Loss: 1.6098, Val Accuracy: 0.1786
Epoch 19/10000, Train Loss: 1.6104, Train Accuracy: 0.1964, Val Loss: 1.6098, Val Accuracy: 0.1786
Epoch 20/10000, Train Loss: 1.6111, Train Accuracy: 0.1908, Val Loss: 1.6098, Val Accuracy: 0.1786
Epoch 21/10000, Train Loss: 1.6097, Train Accuracy: 0.1908, Val Loss: 1.6098, Val Accuracy: 0.1830
Epoch 22/10000, Train Loss: 1.6103, Train Accuracy: 0.2065, Val Loss: 1.6098, Val Accuracy: 0.1830
Epoch 23/10000, Train Loss: 1.6102, Train Accuracy: 0.2054, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 24/10000, Train Loss: 1.6099, Train Accuracy: 0.1975, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 25/10000, Train Loss: 1.6104, Train Accuracy: 0.1830, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 26/10000, Train Loss: 1.6106, Train Accuracy: 0.1741, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 27/10000, Train Loss: 1.6110, Train Accuracy: 0.1696, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 28/10000, Train Loss: 1.6106, Train Accuracy: 0.1975, Val Loss: 1.6097, Val Accuracy: 0.1830
Epoch 29/10000, Train Loss: 1.6109, Train Accuracy: 0.1864, Val Loss: 1.6096, Val Accuracy: 0.1830
Epoch 30/10000, Train Loss: 1.6107, Train Accuracy: 0.1875, Val Loss: 1.6096, Val Accuracy: 0.1830
Epoch 31/10000, Train Loss: 1.6081, Train Accuracy: 0.2288, Val Loss: 1.6096, Val Accuracy: 0.1830
Epoch 32/10000, Train Loss: 1.6104, Train Accuracy: 0.1842, Val Loss: 1.6096, Val Accuracy: 0.1830
Epoch 33/10000, Train Loss: 1.6094, Train Accuracy: 0.1875, Val Loss: 1.6096, Val Accuracy: 0.1830
Epoch 34/10000, Train Loss: 1.6105, Train Accuracy: 0.2020, Val Loss: 1.6095, Val Accuracy: 0.1786
Epoch 35/10000, Train Loss: 1.6103, Train Accuracy: 0.1897, Val Loss: 1.6095, Val Accuracy: 0.1786
Epoch 36/10000, Train Loss: 1.6100, Train Accuracy: 0.2009, Val Loss: 1.6095, Val Accuracy: 0.1786
Epoch 37/10000, Train Loss: 1.6098, Train Accuracy: 0.1842, Val Loss: 1.6095, Val Accuracy: 0.1786
Epoch 38/10000, Train Loss: 1.6093, Train Accuracy: 0.2054, Val Loss: 1.6095, Val Accuracy: 0.1786
Epoch 39/10000, Train Loss: 1.6098, Train Accuracy: 0.2109, Val Loss: 1.6095, Val Accuracy: 0.1830
Epoch 40/10000, Train Loss: 1.6103, Train Accuracy: 0.1964, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 41/10000, Train Loss: 1.6105, Train Accuracy: 0.1987, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 42/10000, Train Loss: 1.6106, Train Accuracy: 0.1797, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 43/10000, Train Loss: 1.6104, Train Accuracy: 0.1864, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 44/10000, Train Loss: 1.6089, Train Accuracy: 0.2020, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 45/10000, Train Loss: 1.6096, Train Accuracy: 0.2087, Val Loss: 1.6094, Val Accuracy: 0.1830
Epoch 46/10000, Train Loss: 1.6091, Train Accuracy: 0.2098, Val Loss: 1.6093, Val Accuracy: 0.1830
Epoch 47/10000, Train Loss: 1.6095, Train Accuracy: 0.2031, Val Loss: 1.6093, Val Accuracy: 0.1830
Epoch 48/10000, Train Loss: 1.6092, Train Accuracy: 0.2121, Val Loss: 1.6093, Val Accuracy: 0.1830
Epoch 49/10000, Train Loss: 1.6097, Train Accuracy: 0.2121, Val Loss: 1.6093, Val Accuracy: 0.1830
Epoch 50/10000, Train Loss: 1.6084, Train Accuracy: 0.2087, Val Loss: 1.6093, Val Accuracy: 0.1875
Epoch 51/10000, Train Loss: 1.6096, Train Accuracy: 0.2109, Val Loss: 1.6093, Val Accuracy: 0.1875
Epoch 52/10000, Train Loss: 1.6085, Train Accuracy: 0.2121, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 53/10000, Train Loss: 1.6099, Train Accuracy: 0.1953, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 54/10000, Train Loss: 1.6091, Train Accuracy: 0.2065, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 55/10000, Train Loss: 1.6086, Train Accuracy: 0.2098, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 56/10000, Train Loss: 1.6092, Train Accuracy: 0.1998, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 57/10000, Train Loss: 1.6101, Train Accuracy: 0.1875, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 58/10000, Train Loss: 1.6104, Train Accuracy: 0.1987, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 59/10000, Train Loss: 1.6095, Train Accuracy: 0.1975, Val Loss: 1.6092, Val Accuracy: 0.1875
Epoch 60/10000, Train Loss: 1.6089, Train Accuracy: 0.1975, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 61/10000, Train Loss: 1.6091, Train Accuracy: 0.2221, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 62/10000, Train Loss: 1.6086, Train Accuracy: 0.2031, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 63/10000, Train Loss: 1.6092, Train Accuracy: 0.2020, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 64/10000, Train Loss: 1.6091, Train Accuracy: 0.2031, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 65/10000, Train Loss: 1.6098, Train Accuracy: 0.1886, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 66/10000, Train Loss: 1.6088, Train Accuracy: 0.2020, Val Loss: 1.6091, Val Accuracy: 0.1875
Epoch 67/10000, Train Loss: 1.6096, Train Accuracy: 0.2154, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 68/10000, Train Loss: 1.6079, Train Accuracy: 0.2031, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 69/10000, Train Loss: 1.6093, Train Accuracy: 0.1998, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 70/10000, Train Loss: 1.6104, Train Accuracy: 0.1920, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 71/10000, Train Loss: 1.6090, Train Accuracy: 0.2232, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 72/10000, Train Loss: 1.6096, Train Accuracy: 0.1931, Val Loss: 1.6090, Val Accuracy: 0.1920
Epoch 73/10000, Train Loss: 1.6098, Train Accuracy: 0.1975, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 74/10000, Train Loss: 1.6097, Train Accuracy: 0.2076, Val Loss: 1.6090, Val Accuracy: 0.1875
Epoch 75/10000, Train Loss: 1.6098, Train Accuracy: 0.2098, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 76/10000, Train Loss: 1.6087, Train Accuracy: 0.2098, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 77/10000, Train Loss: 1.6095, Train Accuracy: 0.1897, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 78/10000, Train Loss: 1.6090, Train Accuracy: 0.2065, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 79/10000, Train Loss: 1.6101, Train Accuracy: 0.2042, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 80/10000, Train Loss: 1.6099, Train Accuracy: 0.2065, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 81/10000, Train Loss: 1.6095, Train Accuracy: 0.1931, Val Loss: 1.6089, Val Accuracy: 0.1920
Epoch 82/10000, Train Loss: 1.6099, Train Accuracy: 0.2009, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 83/10000, Train Loss: 1.6086, Train Accuracy: 0.2232, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 84/10000, Train Loss: 1.6088, Train Accuracy: 0.2143, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 85/10000, Train Loss: 1.6094, Train Accuracy: 0.2121, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 86/10000, Train Loss: 1.6089, Train Accuracy: 0.2076, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 87/10000, Train Loss: 1.6090, Train Accuracy: 0.1953, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 88/10000, Train Loss: 1.6089, Train Accuracy: 0.2076, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 89/10000, Train Loss: 1.6093, Train Accuracy: 0.2176, Val Loss: 1.6088, Val Accuracy: 0.1920
Epoch 90/10000, Train Loss: 1.6094, Train Accuracy: 0.2109, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 91/10000, Train Loss: 1.6082, Train Accuracy: 0.2065, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 92/10000, Train Loss: 1.6093, Train Accuracy: 0.2042, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 93/10000, Train Loss: 1.6081, Train Accuracy: 0.2221, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 94/10000, Train Loss: 1.6073, Train Accuracy: 0.2020, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 95/10000, Train Loss: 1.6086, Train Accuracy: 0.2098, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 96/10000, Train Loss: 1.6079, Train Accuracy: 0.2288, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 97/10000, Train Loss: 1.6096, Train Accuracy: 0.1953, Val Loss: 1.6087, Val Accuracy: 0.1920
Epoch 98/10000, Train Loss: 1.6086, Train Accuracy: 0.2143, Val Loss: 1.6086, Val Accuracy: 0.1920
Epoch 99/10000, Train Loss: 1.6085, Train Accuracy: 0.2188, Val Loss: 1.6086, Val Accuracy: 0.1920
Epoch 100/10000, Train Loss: 1.6098, Train Accuracy: 0.1987, Val Loss: 1.6086, Val Accuracy: 0.1920
Epoch 101/10000, Train Loss: 1.6099, Train Accuracy: 0.1953, Val Loss: 1.6086, Val Accuracy: 0.1964
Epoch 102/10000, Train Loss: 1.6087, Train Accuracy: 0.2176, Val Loss: 1.6086, Val Accuracy: 0.1964
Epoch 103/10000, Train Loss: 1.6086, Train Accuracy: 0.2188, Val Loss: 1.6086, Val Accuracy: 0.1964
Epoch 104/10000, Train Loss: 1.6078, Train Accuracy: 0.2176, Val Loss: 1.6086, Val Accuracy: 0.1964
Epoch 105/10000, Train Loss: 1.6085, Train Accuracy: 0.2299, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 106/10000, Train Loss: 1.6093, Train Accuracy: 0.1886, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 107/10000, Train Loss: 1.6076, Train Accuracy: 0.2254, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 108/10000, Train Loss: 1.6087, Train Accuracy: 0.2221, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 109/10000, Train Loss: 1.6084, Train Accuracy: 0.2121, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 110/10000, Train Loss: 1.6090, Train Accuracy: 0.1920, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 111/10000, Train Loss: 1.6078, Train Accuracy: 0.2221, Val Loss: 1.6085, Val Accuracy: 0.1964
Epoch 112/10000, Train Loss: 1.6085, Train Accuracy: 0.2188, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 113/10000, Train Loss: 1.6092, Train Accuracy: 0.2087, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 114/10000, Train Loss: 1.6091, Train Accuracy: 0.1942, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 115/10000, Train Loss: 1.6080, Train Accuracy: 0.2143, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 116/10000, Train Loss: 1.6083, Train Accuracy: 0.2143, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 117/10000, Train Loss: 1.6084, Train Accuracy: 0.2076, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 118/10000, Train Loss: 1.6081, Train Accuracy: 0.2154, Val Loss: 1.6084, Val Accuracy: 0.1964
Epoch 119/10000, Train Loss: 1.6080, Train Accuracy: 0.2333, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 120/10000, Train Loss: 1.6085, Train Accuracy: 0.1953, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 121/10000, Train Loss: 1.6074, Train Accuracy: 0.2199, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 122/10000, Train Loss: 1.6097, Train Accuracy: 0.1975, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 123/10000, Train Loss: 1.6086, Train Accuracy: 0.2221, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 124/10000, Train Loss: 1.6084, Train Accuracy: 0.2176, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 125/10000, Train Loss: 1.6084, Train Accuracy: 0.2210, Val Loss: 1.6083, Val Accuracy: 0.1964
Epoch 126/10000, Train Loss: 1.6081, Train Accuracy: 0.1942, Val Loss: 1.6082, Val Accuracy: 0.1964
Epoch 127/10000, Train Loss: 1.6078, Train Accuracy: 0.2143, Val Loss: 1.6082, Val Accuracy: 0.1964
Epoch 128/10000, Train Loss: 1.6088, Train Accuracy: 0.2121, Val Loss: 1.6082, Val Accuracy: 0.2009
Epoch 129/10000, Train Loss: 1.6076, Train Accuracy: 0.2288, Val Loss: 1.6082, Val Accuracy: 0.2009
Epoch 130/10000, Train Loss: 1.6075, Train Accuracy: 0.2054, Val Loss: 1.6082, Val Accuracy: 0.2009
Epoch 131/10000, Train Loss: 1.6077, Train Accuracy: 0.2299, Val Loss: 1.6082, Val Accuracy: 0.2009
Epoch 132/10000, Train Loss: 1.6082, Train Accuracy: 0.2009, Val Loss: 1.6082, Val Accuracy: 0.2054
Epoch 133/10000, Train Loss: 1.6081, Train Accuracy: 0.2109, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 134/10000, Train Loss: 1.6089, Train Accuracy: 0.2310, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 135/10000, Train Loss: 1.6086, Train Accuracy: 0.2199, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 136/10000, Train Loss: 1.6085, Train Accuracy: 0.2121, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 137/10000, Train Loss: 1.6087, Train Accuracy: 0.2199, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 138/10000, Train Loss: 1.6083, Train Accuracy: 0.2154, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 139/10000, Train Loss: 1.6083, Train Accuracy: 0.2388, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 140/10000, Train Loss: 1.6084, Train Accuracy: 0.2288, Val Loss: 1.6081, Val Accuracy: 0.2054
Epoch 141/10000, Train Loss: 1.6083, Train Accuracy: 0.2188, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 142/10000, Train Loss: 1.6077, Train Accuracy: 0.2176, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 143/10000, Train Loss: 1.6075, Train Accuracy: 0.2210, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 144/10000, Train Loss: 1.6083, Train Accuracy: 0.2165, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 145/10000, Train Loss: 1.6085, Train Accuracy: 0.2165, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 146/10000, Train Loss: 1.6073, Train Accuracy: 0.2254, Val Loss: 1.6080, Val Accuracy: 0.2054
Epoch 147/10000, Train Loss: 1.6086, Train Accuracy: 0.2266, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 148/10000, Train Loss: 1.6067, Train Accuracy: 0.2299, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 149/10000, Train Loss: 1.6082, Train Accuracy: 0.2121, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 150/10000, Train Loss: 1.6074, Train Accuracy: 0.2433, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 151/10000, Train Loss: 1.6076, Train Accuracy: 0.2098, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 152/10000, Train Loss: 1.6067, Train Accuracy: 0.2556, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 153/10000, Train Loss: 1.6074, Train Accuracy: 0.2154, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 154/10000, Train Loss: 1.6080, Train Accuracy: 0.2221, Val Loss: 1.6079, Val Accuracy: 0.2054
Epoch 155/10000, Train Loss: 1.6077, Train Accuracy: 0.2188, Val Loss: 1.6078, Val Accuracy: 0.2054
Epoch 156/10000, Train Loss: 1.6077, Train Accuracy: 0.2154, Val Loss: 1.6078, Val Accuracy: 0.2054
Epoch 157/10000, Train Loss: 1.6077, Train Accuracy: 0.2109, Val Loss: 1.6078, Val Accuracy: 0.2054
Epoch 158/10000, Train Loss: 1.6073, Train Accuracy: 0.2154, Val Loss: 1.6078, Val Accuracy: 0.2054
Epoch 159/10000, Train Loss: 1.6080, Train Accuracy: 0.2210, Val Loss: 1.6078, Val Accuracy: 0.2054
Epoch 160/10000, Train Loss: 1.6087, Train Accuracy: 0.2165, Val Loss: 1.6078, Val Accuracy: 0.2098
Epoch 161/10000, Train Loss: 1.6071, Train Accuracy: 0.2355, Val Loss: 1.6078, Val Accuracy: 0.2098
Epoch 162/10000, Train Loss: 1.6088, Train Accuracy: 0.1987, Val Loss: 1.6078, Val Accuracy: 0.2098
Epoch 163/10000, Train Loss: 1.6080, Train Accuracy: 0.2176, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 164/10000, Train Loss: 1.6080, Train Accuracy: 0.2232, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 165/10000, Train Loss: 1.6071, Train Accuracy: 0.2165, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 166/10000, Train Loss: 1.6087, Train Accuracy: 0.2221, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 167/10000, Train Loss: 1.6083, Train Accuracy: 0.2121, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 168/10000, Train Loss: 1.6067, Train Accuracy: 0.2321, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 169/10000, Train Loss: 1.6075, Train Accuracy: 0.2232, Val Loss: 1.6077, Val Accuracy: 0.2143
Epoch 170/10000, Train Loss: 1.6082, Train Accuracy: 0.2299, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 171/10000, Train Loss: 1.6070, Train Accuracy: 0.2277, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 172/10000, Train Loss: 1.6068, Train Accuracy: 0.2143, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 173/10000, Train Loss: 1.6071, Train Accuracy: 0.2277, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 174/10000, Train Loss: 1.6083, Train Accuracy: 0.2121, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 175/10000, Train Loss: 1.6079, Train Accuracy: 0.2210, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 176/10000, Train Loss: 1.6082, Train Accuracy: 0.2254, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 177/10000, Train Loss: 1.6073, Train Accuracy: 0.2388, Val Loss: 1.6076, Val Accuracy: 0.2143
Epoch 178/10000, Train Loss: 1.6067, Train Accuracy: 0.2288, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 179/10000, Train Loss: 1.6075, Train Accuracy: 0.2288, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 180/10000, Train Loss: 1.6080, Train Accuracy: 0.2310, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 181/10000, Train Loss: 1.6066, Train Accuracy: 0.2366, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 182/10000, Train Loss: 1.6087, Train Accuracy: 0.2076, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 183/10000, Train Loss: 1.6076, Train Accuracy: 0.2076, Val Loss: 1.6075, Val Accuracy: 0.2143
Epoch 184/10000, Train Loss: 1.6074, Train Accuracy: 0.2132, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 185/10000, Train Loss: 1.6061, Train Accuracy: 0.2288, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 186/10000, Train Loss: 1.6072, Train Accuracy: 0.2221, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 187/10000, Train Loss: 1.6075, Train Accuracy: 0.2254, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 188/10000, Train Loss: 1.6071, Train Accuracy: 0.2377, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 189/10000, Train Loss: 1.6077, Train Accuracy: 0.2455, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 190/10000, Train Loss: 1.6062, Train Accuracy: 0.2388, Val Loss: 1.6074, Val Accuracy: 0.2143
Epoch 191/10000, Train Loss: 1.6083, Train Accuracy: 0.2355, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 192/10000, Train Loss: 1.6070, Train Accuracy: 0.2176, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 193/10000, Train Loss: 1.6075, Train Accuracy: 0.2266, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 194/10000, Train Loss: 1.6077, Train Accuracy: 0.2388, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 195/10000, Train Loss: 1.6071, Train Accuracy: 0.2266, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 196/10000, Train Loss: 1.6062, Train Accuracy: 0.2400, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 197/10000, Train Loss: 1.6079, Train Accuracy: 0.2042, Val Loss: 1.6073, Val Accuracy: 0.2143
Epoch 198/10000, Train Loss: 1.6063, Train Accuracy: 0.2455, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 199/10000, Train Loss: 1.6062, Train Accuracy: 0.2277, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 200/10000, Train Loss: 1.6076, Train Accuracy: 0.2243, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 201/10000, Train Loss: 1.6069, Train Accuracy: 0.2243, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 202/10000, Train Loss: 1.6073, Train Accuracy: 0.2243, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 203/10000, Train Loss: 1.6064, Train Accuracy: 0.2444, Val Loss: 1.6072, Val Accuracy: 0.2188
Epoch 204/10000, Train Loss: 1.6074, Train Accuracy: 0.2243, Val Loss: 1.6072, Val Accuracy: 0.2143
Epoch 205/10000, Train Loss: 1.6066, Train Accuracy: 0.2355, Val Loss: 1.6071, Val Accuracy: 0.2143
Epoch 206/10000, Train Loss: 1.6075, Train Accuracy: 0.2143, Val Loss: 1.6071, Val Accuracy: 0.2188
Epoch 207/10000, Train Loss: 1.6068, Train Accuracy: 0.2422, Val Loss: 1.6071, Val Accuracy: 0.2188
Epoch 208/10000, Train Loss: 1.6069, Train Accuracy: 0.2254, Val Loss: 1.6071, Val Accuracy: 0.2188
Epoch 209/10000, Train Loss: 1.6078, Train Accuracy: 0.2266, Val Loss: 1.6071, Val Accuracy: 0.2188
Epoch 210/10000, Train Loss: 1.6076, Train Accuracy: 0.2121, Val Loss: 1.6071, Val Accuracy: 0.2188
Epoch 211/10000, Train Loss: 1.6074, Train Accuracy: 0.2020, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 212/10000, Train Loss: 1.6069, Train Accuracy: 0.2299, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 213/10000, Train Loss: 1.6071, Train Accuracy: 0.2444, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 214/10000, Train Loss: 1.6068, Train Accuracy: 0.2243, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 215/10000, Train Loss: 1.6071, Train Accuracy: 0.2299, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 216/10000, Train Loss: 1.6064, Train Accuracy: 0.2221, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 217/10000, Train Loss: 1.6069, Train Accuracy: 0.2377, Val Loss: 1.6070, Val Accuracy: 0.2188
Epoch 218/10000, Train Loss: 1.6062, Train Accuracy: 0.2132, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 219/10000, Train Loss: 1.6059, Train Accuracy: 0.2388, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 220/10000, Train Loss: 1.6069, Train Accuracy: 0.2254, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 221/10000, Train Loss: 1.6063, Train Accuracy: 0.2455, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 222/10000, Train Loss: 1.6074, Train Accuracy: 0.2344, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 223/10000, Train Loss: 1.6055, Train Accuracy: 0.2455, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 224/10000, Train Loss: 1.6065, Train Accuracy: 0.2277, Val Loss: 1.6069, Val Accuracy: 0.2188
Epoch 225/10000, Train Loss: 1.6068, Train Accuracy: 0.2333, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 226/10000, Train Loss: 1.6071, Train Accuracy: 0.2154, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 227/10000, Train Loss: 1.6066, Train Accuracy: 0.2411, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 228/10000, Train Loss: 1.6070, Train Accuracy: 0.2310, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 229/10000, Train Loss: 1.6070, Train Accuracy: 0.2321, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 230/10000, Train Loss: 1.6080, Train Accuracy: 0.2344, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 231/10000, Train Loss: 1.6064, Train Accuracy: 0.2400, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 232/10000, Train Loss: 1.6059, Train Accuracy: 0.2433, Val Loss: 1.6068, Val Accuracy: 0.2188
Epoch 233/10000, Train Loss: 1.6070, Train Accuracy: 0.2411, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 234/10000, Train Loss: 1.6063, Train Accuracy: 0.2422, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 235/10000, Train Loss: 1.6075, Train Accuracy: 0.2165, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 236/10000, Train Loss: 1.6066, Train Accuracy: 0.2355, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 237/10000, Train Loss: 1.6073, Train Accuracy: 0.2299, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 238/10000, Train Loss: 1.6070, Train Accuracy: 0.2310, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 239/10000, Train Loss: 1.6073, Train Accuracy: 0.2310, Val Loss: 1.6067, Val Accuracy: 0.2188
Epoch 240/10000, Train Loss: 1.6065, Train Accuracy: 0.2444, Val Loss: 1.6066, Val Accuracy: 0.2188
Epoch 241/10000, Train Loss: 1.6071, Train Accuracy: 0.2277, Val Loss: 1.6066, Val Accuracy: 0.2188
Epoch 242/10000, Train Loss: 1.6066, Train Accuracy: 0.2522, Val Loss: 1.6066, Val Accuracy: 0.2188
Epoch 243/10000, Train Loss: 1.6061, Train Accuracy: 0.2511, Val Loss: 1.6066, Val Accuracy: 0.2188
Epoch 244/10000, Train Loss: 1.6061, Train Accuracy: 0.2589, Val Loss: 1.6066, Val Accuracy: 0.2188
Epoch 245/10000, Train Loss: 1.6052, Train Accuracy: 0.2556, Val Loss: 1.6065, Val Accuracy: 0.2188
Epoch 246/10000, Train Loss: 1.6053, Train Accuracy: 0.2500, Val Loss: 1.6065, Val Accuracy: 0.2188
Epoch 247/10000, Train Loss: 1.6061, Train Accuracy: 0.2333, Val Loss: 1.6065, Val Accuracy: 0.2188
Epoch 248/10000, Train Loss: 1.6080, Train Accuracy: 0.2210, Val Loss: 1.6065, Val Accuracy: 0.2188
Epoch 249/10000, Train Loss: 1.6072, Train Accuracy: 0.2344, Val Loss: 1.6065, Val Accuracy: 0.2188
Epoch 250/10000, Train Loss: 1.6064, Train Accuracy: 0.2344, Val Loss: 1.6065, Val Accuracy: 0.2232
Epoch 251/10000, Train Loss: 1.6065, Train Accuracy: 0.2478, Val Loss: 1.6065, Val Accuracy: 0.2232
Epoch 252/10000, Train Loss: 1.6060, Train Accuracy: 0.2489, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 253/10000, Train Loss: 1.6068, Train Accuracy: 0.2478, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 254/10000, Train Loss: 1.6054, Train Accuracy: 0.2600, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 255/10000, Train Loss: 1.6071, Train Accuracy: 0.2310, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 256/10000, Train Loss: 1.6064, Train Accuracy: 0.2243, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 257/10000, Train Loss: 1.6053, Train Accuracy: 0.2578, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 258/10000, Train Loss: 1.6052, Train Accuracy: 0.2422, Val Loss: 1.6064, Val Accuracy: 0.2232
Epoch 259/10000, Train Loss: 1.6057, Train Accuracy: 0.2478, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 260/10000, Train Loss: 1.6064, Train Accuracy: 0.2478, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 261/10000, Train Loss: 1.6052, Train Accuracy: 0.2567, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 262/10000, Train Loss: 1.6056, Train Accuracy: 0.2511, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 263/10000, Train Loss: 1.6060, Train Accuracy: 0.2388, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 264/10000, Train Loss: 1.6059, Train Accuracy: 0.2455, Val Loss: 1.6063, Val Accuracy: 0.2232
Epoch 265/10000, Train Loss: 1.6057, Train Accuracy: 0.2467, Val Loss: 1.6063, Val Accuracy: 0.2277
Epoch 266/10000, Train Loss: 1.6074, Train Accuracy: 0.2299, Val Loss: 1.6062, Val Accuracy: 0.2277
Epoch 267/10000, Train Loss: 1.6055, Train Accuracy: 0.2344, Val Loss: 1.6062, Val Accuracy: 0.2277
Epoch 268/10000, Train Loss: 1.6061, Train Accuracy: 0.2266, Val Loss: 1.6062, Val Accuracy: 0.2277
Epoch 269/10000, Train Loss: 1.6064, Train Accuracy: 0.2366, Val Loss: 1.6062, Val Accuracy: 0.2232
Epoch 270/10000, Train Loss: 1.6060, Train Accuracy: 0.2333, Val Loss: 1.6062, Val Accuracy: 0.2232
Epoch 271/10000, Train Loss: 1.6049, Train Accuracy: 0.2522, Val Loss: 1.6062, Val Accuracy: 0.2277
Epoch 272/10000, Train Loss: 1.6058, Train Accuracy: 0.2500, Val Loss: 1.6061, Val Accuracy: 0.2232
Epoch 273/10000, Train Loss: 1.6057, Train Accuracy: 0.2254, Val Loss: 1.6061, Val Accuracy: 0.2277
Epoch 274/10000, Train Loss: 1.6063, Train Accuracy: 0.2600, Val Loss: 1.6061, Val Accuracy: 0.2277
Epoch 275/10000, Train Loss: 1.6059, Train Accuracy: 0.2433, Val Loss: 1.6061, Val Accuracy: 0.2232
Epoch 276/10000, Train Loss: 1.6068, Train Accuracy: 0.2344, Val Loss: 1.6061, Val Accuracy: 0.2277
Epoch 277/10000, Train Loss: 1.6064, Train Accuracy: 0.2321, Val Loss: 1.6061, Val Accuracy: 0.2232
Epoch 278/10000, Train Loss: 1.6066, Train Accuracy: 0.2254, Val Loss: 1.6061, Val Accuracy: 0.2232
Epoch 279/10000, Train Loss: 1.6059, Train Accuracy: 0.2377, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 280/10000, Train Loss: 1.6058, Train Accuracy: 0.2299, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 281/10000, Train Loss: 1.6051, Train Accuracy: 0.2578, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 282/10000, Train Loss: 1.6058, Train Accuracy: 0.2210, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 283/10000, Train Loss: 1.6050, Train Accuracy: 0.2623, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 284/10000, Train Loss: 1.6046, Train Accuracy: 0.2545, Val Loss: 1.6060, Val Accuracy: 0.2232
Epoch 285/10000, Train Loss: 1.6055, Train Accuracy: 0.2578, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 286/10000, Train Loss: 1.6057, Train Accuracy: 0.2467, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 287/10000, Train Loss: 1.6058, Train Accuracy: 0.2500, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 288/10000, Train Loss: 1.6054, Train Accuracy: 0.2533, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 289/10000, Train Loss: 1.6058, Train Accuracy: 0.2600, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 290/10000, Train Loss: 1.6051, Train Accuracy: 0.2500, Val Loss: 1.6059, Val Accuracy: 0.2232
Epoch 291/10000, Train Loss: 1.6059, Train Accuracy: 0.2310, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 292/10000, Train Loss: 1.6054, Train Accuracy: 0.2310, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 293/10000, Train Loss: 1.6042, Train Accuracy: 0.2634, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 294/10000, Train Loss: 1.6057, Train Accuracy: 0.2377, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 295/10000, Train Loss: 1.6056, Train Accuracy: 0.2355, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 296/10000, Train Loss: 1.6059, Train Accuracy: 0.2288, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 297/10000, Train Loss: 1.6055, Train Accuracy: 0.2377, Val Loss: 1.6058, Val Accuracy: 0.2232
Epoch 298/10000, Train Loss: 1.6063, Train Accuracy: 0.2422, Val Loss: 1.6057, Val Accuracy: 0.2232
Epoch 299/10000, Train Loss: 1.6059, Train Accuracy: 0.2634, Val Loss: 1.6057, Val Accuracy: 0.2232
Epoch 300/10000, Train Loss: 1.6066, Train Accuracy: 0.2377, Val Loss: 1.6057, Val Accuracy: 0.2232
Epoch 301/10000, Train Loss: 1.6042, Train Accuracy: 0.2623, Val Loss: 1.6057, Val Accuracy: 0.2277
Epoch 302/10000, Train Loss: 1.6061, Train Accuracy: 0.2511, Val Loss: 1.6057, Val Accuracy: 0.2277
Epoch 303/10000, Train Loss: 1.6053, Train Accuracy: 0.2533, Val Loss: 1.6057, Val Accuracy: 0.2277
Epoch 304/10000, Train Loss: 1.6061, Train Accuracy: 0.2321, Val Loss: 1.6056, Val Accuracy: 0.2277
Epoch 305/10000, Train Loss: 1.6062, Train Accuracy: 0.2433, Val Loss: 1.6056, Val Accuracy: 0.2277
Epoch 306/10000, Train Loss: 1.6060, Train Accuracy: 0.2299, Val Loss: 1.6056, Val Accuracy: 0.2277
Epoch 307/10000, Train Loss: 1.6056, Train Accuracy: 0.2422, Val Loss: 1.6056, Val Accuracy: 0.2277
Epoch 308/10000, Train Loss: 1.6057, Train Accuracy: 0.2400, Val Loss: 1.6056, Val Accuracy: 0.2277
Epoch 309/10000, Train Loss: 1.6059, Train Accuracy: 0.2511, Val Loss: 1.6056, Val Accuracy: 0.2321
Epoch 310/10000, Train Loss: 1.6041, Train Accuracy: 0.2768, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 311/10000, Train Loss: 1.6043, Train Accuracy: 0.2667, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 312/10000, Train Loss: 1.6065, Train Accuracy: 0.2433, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 313/10000, Train Loss: 1.6048, Train Accuracy: 0.2589, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 314/10000, Train Loss: 1.6051, Train Accuracy: 0.2478, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 315/10000, Train Loss: 1.6044, Train Accuracy: 0.2522, Val Loss: 1.6055, Val Accuracy: 0.2321
Epoch 316/10000, Train Loss: 1.6048, Train Accuracy: 0.2388, Val Loss: 1.6054, Val Accuracy: 0.2321
Epoch 317/10000, Train Loss: 1.6046, Train Accuracy: 0.2645, Val Loss: 1.6054, Val Accuracy: 0.2321
Epoch 318/10000, Train Loss: 1.6046, Train Accuracy: 0.2589, Val Loss: 1.6054, Val Accuracy: 0.2321
Epoch 319/10000, Train Loss: 1.6039, Train Accuracy: 0.2589, Val Loss: 1.6054, Val Accuracy: 0.2321
Epoch 320/10000, Train Loss: 1.6034, Train Accuracy: 0.2623, Val Loss: 1.6054, Val Accuracy: 0.2321
Epoch 321/10000, Train Loss: 1.6050, Train Accuracy: 0.2589, Val Loss: 1.6054, Val Accuracy: 0.2277
Epoch 322/10000, Train Loss: 1.6055, Train Accuracy: 0.2455, Val Loss: 1.6054, Val Accuracy: 0.2277
Epoch 323/10000, Train Loss: 1.6049, Train Accuracy: 0.2701, Val Loss: 1.6053, Val Accuracy: 0.2277
Epoch 324/10000, Train Loss: 1.6051, Train Accuracy: 0.2467, Val Loss: 1.6053, Val Accuracy: 0.2277
Epoch 325/10000, Train Loss: 1.6059, Train Accuracy: 0.2545, Val Loss: 1.6053, Val Accuracy: 0.2366
Epoch 326/10000, Train Loss: 1.6046, Train Accuracy: 0.2556, Val Loss: 1.6053, Val Accuracy: 0.2366
Epoch 327/10000, Train Loss: 1.6063, Train Accuracy: 0.2411, Val Loss: 1.6053, Val Accuracy: 0.2366
Epoch 328/10000, Train Loss: 1.6056, Train Accuracy: 0.2433, Val Loss: 1.6053, Val Accuracy: 0.2321
Epoch 329/10000, Train Loss: 1.6049, Train Accuracy: 0.2511, Val Loss: 1.6052, Val Accuracy: 0.2366
Epoch 330/10000, Train Loss: 1.6047, Train Accuracy: 0.2768, Val Loss: 1.6052, Val Accuracy: 0.2366
Epoch 331/10000, Train Loss: 1.6056, Train Accuracy: 0.2411, Val Loss: 1.6052, Val Accuracy: 0.2366
Epoch 332/10000, Train Loss: 1.6054, Train Accuracy: 0.2444, Val Loss: 1.6052, Val Accuracy: 0.2366
Epoch 333/10000, Train Loss: 1.6050, Train Accuracy: 0.2377, Val Loss: 1.6052, Val Accuracy: 0.2366
Epoch 334/10000, Train Loss: 1.6055, Train Accuracy: 0.2377, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 335/10000, Train Loss: 1.6065, Train Accuracy: 0.2388, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 336/10000, Train Loss: 1.6048, Train Accuracy: 0.2478, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 337/10000, Train Loss: 1.6044, Train Accuracy: 0.2567, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 338/10000, Train Loss: 1.6040, Train Accuracy: 0.2701, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 339/10000, Train Loss: 1.6051, Train Accuracy: 0.2422, Val Loss: 1.6051, Val Accuracy: 0.2366
Epoch 340/10000, Train Loss: 1.6051, Train Accuracy: 0.2746, Val Loss: 1.6050, Val Accuracy: 0.2366
Epoch 341/10000, Train Loss: 1.6045, Train Accuracy: 0.2567, Val Loss: 1.6050, Val Accuracy: 0.2411
Epoch 342/10000, Train Loss: 1.6046, Train Accuracy: 0.2567, Val Loss: 1.6050, Val Accuracy: 0.2455
Epoch 343/10000, Train Loss: 1.6029, Train Accuracy: 0.2600, Val Loss: 1.6050, Val Accuracy: 0.2455
Epoch 344/10000, Train Loss: 1.6039, Train Accuracy: 0.2667, Val Loss: 1.6050, Val Accuracy: 0.2455
Epoch 345/10000, Train Loss: 1.6062, Train Accuracy: 0.2511, Val Loss: 1.6050, Val Accuracy: 0.2500
Epoch 346/10000, Train Loss: 1.6036, Train Accuracy: 0.2444, Val Loss: 1.6050, Val Accuracy: 0.2455
Epoch 347/10000, Train Loss: 1.6041, Train Accuracy: 0.2600, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 348/10000, Train Loss: 1.6048, Train Accuracy: 0.2723, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 349/10000, Train Loss: 1.6055, Train Accuracy: 0.2545, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 350/10000, Train Loss: 1.6054, Train Accuracy: 0.2366, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 351/10000, Train Loss: 1.6058, Train Accuracy: 0.2567, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 352/10000, Train Loss: 1.6032, Train Accuracy: 0.2757, Val Loss: 1.6049, Val Accuracy: 0.2500
Epoch 353/10000, Train Loss: 1.6052, Train Accuracy: 0.2645, Val Loss: 1.6049, Val Accuracy: 0.2545
Epoch 354/10000, Train Loss: 1.6037, Train Accuracy: 0.2690, Val Loss: 1.6048, Val Accuracy: 0.2500
Epoch 355/10000, Train Loss: 1.6050, Train Accuracy: 0.2567, Val Loss: 1.6048, Val Accuracy: 0.2500
Epoch 356/10000, Train Loss: 1.6044, Train Accuracy: 0.2567, Val Loss: 1.6048, Val Accuracy: 0.2545
Epoch 357/10000, Train Loss: 1.6044, Train Accuracy: 0.2723, Val Loss: 1.6048, Val Accuracy: 0.2545
Epoch 358/10000, Train Loss: 1.6032, Train Accuracy: 0.2656, Val Loss: 1.6048, Val Accuracy: 0.2545
Epoch 359/10000, Train Loss: 1.6046, Train Accuracy: 0.2489, Val Loss: 1.6047, Val Accuracy: 0.2545
Epoch 360/10000, Train Loss: 1.6052, Train Accuracy: 0.2578, Val Loss: 1.6047, Val Accuracy: 0.2545
Epoch 361/10000, Train Loss: 1.6045, Train Accuracy: 0.2645, Val Loss: 1.6047, Val Accuracy: 0.2545
Epoch 362/10000, Train Loss: 1.6045, Train Accuracy: 0.2868, Val Loss: 1.6047, Val Accuracy: 0.2545
Epoch 363/10000, Train Loss: 1.6038, Train Accuracy: 0.2712, Val Loss: 1.6047, Val Accuracy: 0.2545
Epoch 364/10000, Train Loss: 1.6041, Train Accuracy: 0.2690, Val Loss: 1.6047, Val Accuracy: 0.2589
Epoch 365/10000, Train Loss: 1.6054, Train Accuracy: 0.2567, Val Loss: 1.6047, Val Accuracy: 0.2589
Epoch 366/10000, Train Loss: 1.6047, Train Accuracy: 0.2478, Val Loss: 1.6046, Val Accuracy: 0.2589
Epoch 367/10000, Train Loss: 1.6045, Train Accuracy: 0.2500, Val Loss: 1.6046, Val Accuracy: 0.2589
Epoch 368/10000, Train Loss: 1.6030, Train Accuracy: 0.2757, Val Loss: 1.6046, Val Accuracy: 0.2589
Epoch 369/10000, Train Loss: 1.6040, Train Accuracy: 0.2522, Val Loss: 1.6046, Val Accuracy: 0.2589
Epoch 370/10000, Train Loss: 1.6042, Train Accuracy: 0.2768, Val Loss: 1.6046, Val Accuracy: 0.2589
Epoch 371/10000, Train Loss: 1.6047, Train Accuracy: 0.2455, Val Loss: 1.6045, Val Accuracy: 0.2589
Epoch 372/10000, Train Loss: 1.6041, Train Accuracy: 0.2734, Val Loss: 1.6045, Val Accuracy: 0.2589
Epoch 373/10000, Train Loss: 1.6047, Train Accuracy: 0.2455, Val Loss: 1.6045, Val Accuracy: 0.2589
Epoch 374/10000, Train Loss: 1.6022, Train Accuracy: 0.2812, Val Loss: 1.6045, Val Accuracy: 0.2589
Epoch 375/10000, Train Loss: 1.6041, Train Accuracy: 0.2612, Val Loss: 1.6045, Val Accuracy: 0.2589
Epoch 376/10000, Train Loss: 1.6039, Train Accuracy: 0.2812, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 377/10000, Train Loss: 1.6043, Train Accuracy: 0.2478, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 378/10000, Train Loss: 1.6037, Train Accuracy: 0.2690, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 379/10000, Train Loss: 1.6035, Train Accuracy: 0.2645, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 380/10000, Train Loss: 1.6035, Train Accuracy: 0.2812, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 381/10000, Train Loss: 1.6032, Train Accuracy: 0.2612, Val Loss: 1.6044, Val Accuracy: 0.2589
Epoch 382/10000, Train Loss: 1.6042, Train Accuracy: 0.2801, Val Loss: 1.6043, Val Accuracy: 0.2589
Epoch 383/10000, Train Loss: 1.6038, Train Accuracy: 0.2634, Val Loss: 1.6043, Val Accuracy: 0.2589
Epoch 384/10000, Train Loss: 1.6043, Train Accuracy: 0.2522, Val Loss: 1.6043, Val Accuracy: 0.2589
Epoch 385/10000, Train Loss: 1.6029, Train Accuracy: 0.2779, Val Loss: 1.6043, Val Accuracy: 0.2589
Epoch 386/10000, Train Loss: 1.6033, Train Accuracy: 0.2533, Val Loss: 1.6043, Val Accuracy: 0.2589
Epoch 387/10000, Train Loss: 1.6042, Train Accuracy: 0.2801, Val Loss: 1.6042, Val Accuracy: 0.2589
Epoch 388/10000, Train Loss: 1.6031, Train Accuracy: 0.2690, Val Loss: 1.6042, Val Accuracy: 0.2589
Epoch 389/10000, Train Loss: 1.6052, Train Accuracy: 0.2511, Val Loss: 1.6042, Val Accuracy: 0.2589
Epoch 390/10000, Train Loss: 1.6048, Train Accuracy: 0.2522, Val Loss: 1.6042, Val Accuracy: 0.2589
Epoch 391/10000, Train Loss: 1.6027, Train Accuracy: 0.2846, Val Loss: 1.6042, Val Accuracy: 0.2589
Epoch 392/10000, Train Loss: 1.6031, Train Accuracy: 0.2734, Val Loss: 1.6041, Val Accuracy: 0.2589
Epoch 393/10000, Train Loss: 1.6039, Train Accuracy: 0.2824, Val Loss: 1.6041, Val Accuracy: 0.2634
Epoch 394/10000, Train Loss: 1.6032, Train Accuracy: 0.2801, Val Loss: 1.6041, Val Accuracy: 0.2634
Epoch 395/10000, Train Loss: 1.6038, Train Accuracy: 0.2734, Val Loss: 1.6041, Val Accuracy: 0.2634
Epoch 396/10000, Train Loss: 1.6027, Train Accuracy: 0.2868, Val Loss: 1.6041, Val Accuracy: 0.2634
Epoch 397/10000, Train Loss: 1.6037, Train Accuracy: 0.2656, Val Loss: 1.6041, Val Accuracy: 0.2589
Epoch 398/10000, Train Loss: 1.6035, Train Accuracy: 0.2790, Val Loss: 1.6040, Val Accuracy: 0.2634
Epoch 399/10000, Train Loss: 1.6031, Train Accuracy: 0.2645, Val Loss: 1.6040, Val Accuracy: 0.2589
Epoch 400/10000, Train Loss: 1.6033, Train Accuracy: 0.2891, Val Loss: 1.6040, Val Accuracy: 0.2589
Epoch 401/10000, Train Loss: 1.6030, Train Accuracy: 0.2779, Val Loss: 1.6040, Val Accuracy: 0.2589
Epoch 402/10000, Train Loss: 1.6025, Train Accuracy: 0.2913, Val Loss: 1.6040, Val Accuracy: 0.2589
Epoch 403/10000, Train Loss: 1.6040, Train Accuracy: 0.2578, Val Loss: 1.6040, Val Accuracy: 0.2589
Epoch 404/10000, Train Loss: 1.6029, Train Accuracy: 0.2667, Val Loss: 1.6039, Val Accuracy: 0.2589
Epoch 405/10000, Train Loss: 1.6032, Train Accuracy: 0.2790, Val Loss: 1.6039, Val Accuracy: 0.2634
Epoch 406/10000, Train Loss: 1.6027, Train Accuracy: 0.2801, Val Loss: 1.6039, Val Accuracy: 0.2634
Epoch 407/10000, Train Loss: 1.6049, Train Accuracy: 0.2511, Val Loss: 1.6039, Val Accuracy: 0.2634
Epoch 408/10000, Train Loss: 1.6032, Train Accuracy: 0.2667, Val Loss: 1.6039, Val Accuracy: 0.2634
Epoch 409/10000, Train Loss: 1.6029, Train Accuracy: 0.2801, Val Loss: 1.6039, Val Accuracy: 0.2634
Epoch 410/10000, Train Loss: 1.6028, Train Accuracy: 0.2623, Val Loss: 1.6038, Val Accuracy: 0.2634
Epoch 411/10000, Train Loss: 1.6038, Train Accuracy: 0.2824, Val Loss: 1.6038, Val Accuracy: 0.2634
Epoch 412/10000, Train Loss: 1.6045, Train Accuracy: 0.2656, Val Loss: 1.6038, Val Accuracy: 0.2679
Epoch 413/10000, Train Loss: 1.6029, Train Accuracy: 0.2712, Val Loss: 1.6038, Val Accuracy: 0.2679
Epoch 414/10000, Train Loss: 1.6039, Train Accuracy: 0.2612, Val Loss: 1.6038, Val Accuracy: 0.2679
Epoch 415/10000, Train Loss: 1.6043, Train Accuracy: 0.2690, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 416/10000, Train Loss: 1.6034, Train Accuracy: 0.2969, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 417/10000, Train Loss: 1.6035, Train Accuracy: 0.2589, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 418/10000, Train Loss: 1.6025, Train Accuracy: 0.2612, Val Loss: 1.6037, Val Accuracy: 0.2634
Epoch 419/10000, Train Loss: 1.6032, Train Accuracy: 0.2634, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 420/10000, Train Loss: 1.6032, Train Accuracy: 0.2879, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 421/10000, Train Loss: 1.6037, Train Accuracy: 0.2701, Val Loss: 1.6037, Val Accuracy: 0.2679
Epoch 422/10000, Train Loss: 1.6036, Train Accuracy: 0.2701, Val Loss: 1.6036, Val Accuracy: 0.2723
Epoch 423/10000, Train Loss: 1.6028, Train Accuracy: 0.2656, Val Loss: 1.6036, Val Accuracy: 0.2768
Epoch 424/10000, Train Loss: 1.6033, Train Accuracy: 0.2667, Val Loss: 1.6036, Val Accuracy: 0.2768
Epoch 425/10000, Train Loss: 1.6033, Train Accuracy: 0.2779, Val Loss: 1.6036, Val Accuracy: 0.2768
Epoch 426/10000, Train Loss: 1.6033, Train Accuracy: 0.2623, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 427/10000, Train Loss: 1.6035, Train Accuracy: 0.2645, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 428/10000, Train Loss: 1.6024, Train Accuracy: 0.2868, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 429/10000, Train Loss: 1.6024, Train Accuracy: 0.2924, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 430/10000, Train Loss: 1.6026, Train Accuracy: 0.2857, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 431/10000, Train Loss: 1.6037, Train Accuracy: 0.2746, Val Loss: 1.6035, Val Accuracy: 0.2768
Epoch 432/10000, Train Loss: 1.6035, Train Accuracy: 0.2690, Val Loss: 1.6035, Val Accuracy: 0.2812
Epoch 433/10000, Train Loss: 1.6029, Train Accuracy: 0.2757, Val Loss: 1.6034, Val Accuracy: 0.2812
Epoch 434/10000, Train Loss: 1.6027, Train Accuracy: 0.2969, Val Loss: 1.6034, Val Accuracy: 0.2812
Epoch 435/10000, Train Loss: 1.6019, Train Accuracy: 0.2835, Val Loss: 1.6034, Val Accuracy: 0.2812
Epoch 436/10000, Train Loss: 1.6024, Train Accuracy: 0.2790, Val Loss: 1.6034, Val Accuracy: 0.2812
Epoch 437/10000, Train Loss: 1.6029, Train Accuracy: 0.2913, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 438/10000, Train Loss: 1.6020, Train Accuracy: 0.2924, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 439/10000, Train Loss: 1.6028, Train Accuracy: 0.2935, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 440/10000, Train Loss: 1.6022, Train Accuracy: 0.2768, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 441/10000, Train Loss: 1.6031, Train Accuracy: 0.2835, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 442/10000, Train Loss: 1.6033, Train Accuracy: 0.2801, Val Loss: 1.6033, Val Accuracy: 0.2812
Epoch 443/10000, Train Loss: 1.6029, Train Accuracy: 0.2835, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 444/10000, Train Loss: 1.6029, Train Accuracy: 0.2779, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 445/10000, Train Loss: 1.6028, Train Accuracy: 0.2891, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 446/10000, Train Loss: 1.6026, Train Accuracy: 0.2790, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 447/10000, Train Loss: 1.6019, Train Accuracy: 0.2935, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 448/10000, Train Loss: 1.6040, Train Accuracy: 0.2824, Val Loss: 1.6032, Val Accuracy: 0.2812
Epoch 449/10000, Train Loss: 1.6027, Train Accuracy: 0.2801, Val Loss: 1.6031, Val Accuracy: 0.2768
Epoch 450/10000, Train Loss: 1.6035, Train Accuracy: 0.2868, Val Loss: 1.6031, Val Accuracy: 0.2768
Epoch 451/10000, Train Loss: 1.6022, Train Accuracy: 0.2790, Val Loss: 1.6031, Val Accuracy: 0.2768
Epoch 452/10000, Train Loss: 1.6028, Train Accuracy: 0.2634, Val Loss: 1.6031, Val Accuracy: 0.2768
Epoch 453/10000, Train Loss: 1.6035, Train Accuracy: 0.2567, Val Loss: 1.6030, Val Accuracy: 0.2768
Epoch 454/10000, Train Loss: 1.6022, Train Accuracy: 0.2679, Val Loss: 1.6030, Val Accuracy: 0.2768
Epoch 455/10000, Train Loss: 1.6034, Train Accuracy: 0.2533, Val Loss: 1.6030, Val Accuracy: 0.2768
Epoch 456/10000, Train Loss: 1.6030, Train Accuracy: 0.2835, Val Loss: 1.6030, Val Accuracy: 0.2768
Epoch 457/10000, Train Loss: 1.6022, Train Accuracy: 0.2824, Val Loss: 1.6030, Val Accuracy: 0.2768
Epoch 458/10000, Train Loss: 1.6022, Train Accuracy: 0.2757, Val Loss: 1.6029, Val Accuracy: 0.2768
Epoch 459/10000, Train Loss: 1.6027, Train Accuracy: 0.2723, Val Loss: 1.6029, Val Accuracy: 0.2768
Epoch 460/10000, Train Loss: 1.6022, Train Accuracy: 0.2790, Val Loss: 1.6029, Val Accuracy: 0.2768
Epoch 461/10000, Train Loss: 1.6024, Train Accuracy: 0.2623, Val Loss: 1.6029, Val Accuracy: 0.2768
Epoch 462/10000, Train Loss: 1.6019, Train Accuracy: 0.2801, Val Loss: 1.6029, Val Accuracy: 0.2768
Epoch 463/10000, Train Loss: 1.6028, Train Accuracy: 0.2701, Val Loss: 1.6028, Val Accuracy: 0.2768
Epoch 464/10000, Train Loss: 1.6023, Train Accuracy: 0.2723, Val Loss: 1.6028, Val Accuracy: 0.2768
Epoch 465/10000, Train Loss: 1.6017, Train Accuracy: 0.2902, Val Loss: 1.6028, Val Accuracy: 0.2768
Epoch 466/10000, Train Loss: 1.6029, Train Accuracy: 0.2913, Val Loss: 1.6028, Val Accuracy: 0.2768
Epoch 467/10000, Train Loss: 1.6013, Train Accuracy: 0.2958, Val Loss: 1.6028, Val Accuracy: 0.2768
Epoch 468/10000, Train Loss: 1.6026, Train Accuracy: 0.2690, Val Loss: 1.6027, Val Accuracy: 0.2768
Epoch 469/10000, Train Loss: 1.6020, Train Accuracy: 0.2913, Val Loss: 1.6027, Val Accuracy: 0.2768
Epoch 470/10000, Train Loss: 1.6020, Train Accuracy: 0.2779, Val Loss: 1.6027, Val Accuracy: 0.2768
Epoch 471/10000, Train Loss: 1.6019, Train Accuracy: 0.2667, Val Loss: 1.6027, Val Accuracy: 0.2812
Epoch 472/10000, Train Loss: 1.6012, Train Accuracy: 0.2913, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 473/10000, Train Loss: 1.6025, Train Accuracy: 0.2891, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 474/10000, Train Loss: 1.6013, Train Accuracy: 0.2656, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 475/10000, Train Loss: 1.6028, Train Accuracy: 0.2824, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 476/10000, Train Loss: 1.6025, Train Accuracy: 0.2768, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 477/10000, Train Loss: 1.5996, Train Accuracy: 0.3281, Val Loss: 1.6026, Val Accuracy: 0.2812
Epoch 478/10000, Train Loss: 1.6025, Train Accuracy: 0.2801, Val Loss: 1.6025, Val Accuracy: 0.2812
Epoch 479/10000, Train Loss: 1.6014, Train Accuracy: 0.3069, Val Loss: 1.6025, Val Accuracy: 0.2812
Epoch 480/10000, Train Loss: 1.6015, Train Accuracy: 0.2991, Val Loss: 1.6025, Val Accuracy: 0.2812
Epoch 481/10000, Train Loss: 1.6020, Train Accuracy: 0.2935, Val Loss: 1.6025, Val Accuracy: 0.2812
Epoch 482/10000, Train Loss: 1.6026, Train Accuracy: 0.2556, Val Loss: 1.6025, Val Accuracy: 0.2857
Epoch 483/10000, Train Loss: 1.6026, Train Accuracy: 0.2589, Val Loss: 1.6024, Val Accuracy: 0.2857
Epoch 484/10000, Train Loss: 1.6022, Train Accuracy: 0.2779, Val Loss: 1.6024, Val Accuracy: 0.2857
Epoch 485/10000, Train Loss: 1.6029, Train Accuracy: 0.2746, Val Loss: 1.6024, Val Accuracy: 0.2902
Epoch 486/10000, Train Loss: 1.6030, Train Accuracy: 0.2757, Val Loss: 1.6024, Val Accuracy: 0.2902
Epoch 487/10000, Train Loss: 1.6024, Train Accuracy: 0.2857, Val Loss: 1.6024, Val Accuracy: 0.2902
Epoch 488/10000, Train Loss: 1.6021, Train Accuracy: 0.2768, Val Loss: 1.6023, Val Accuracy: 0.2902
Epoch 489/10000, Train Loss: 1.6036, Train Accuracy: 0.2600, Val Loss: 1.6023, Val Accuracy: 0.2902
Epoch 490/10000, Train Loss: 1.6010, Train Accuracy: 0.2902, Val Loss: 1.6023, Val Accuracy: 0.2902
Epoch 491/10000, Train Loss: 1.6014, Train Accuracy: 0.2891, Val Loss: 1.6023, Val Accuracy: 0.2902
Epoch 492/10000, Train Loss: 1.6021, Train Accuracy: 0.2879, Val Loss: 1.6023, Val Accuracy: 0.2946
Epoch 493/10000, Train Loss: 1.6021, Train Accuracy: 0.2946, Val Loss: 1.6022, Val Accuracy: 0.2946
Epoch 494/10000, Train Loss: 1.6019, Train Accuracy: 0.2790, Val Loss: 1.6022, Val Accuracy: 0.2946
Epoch 495/10000, Train Loss: 1.6021, Train Accuracy: 0.2991, Val Loss: 1.6022, Val Accuracy: 0.2946
Epoch 496/10000, Train Loss: 1.6027, Train Accuracy: 0.2768, Val Loss: 1.6022, Val Accuracy: 0.2946
Epoch 497/10000, Train Loss: 1.6016, Train Accuracy: 0.2991, Val Loss: 1.6022, Val Accuracy: 0.2946
Epoch 498/10000, Train Loss: 1.6016, Train Accuracy: 0.2701, Val Loss: 1.6021, Val Accuracy: 0.2946
Epoch 499/10000, Train Loss: 1.6009, Train Accuracy: 0.3036, Val Loss: 1.6021, Val Accuracy: 0.2946
Epoch 500/10000, Train Loss: 1.6003, Train Accuracy: 0.2790, Val Loss: 1.6021, Val Accuracy: 0.2991
Epoch 501/10000, Train Loss: 1.6010, Train Accuracy: 0.2935, Val Loss: 1.6021, Val Accuracy: 0.2991
Epoch 502/10000, Train Loss: 1.6005, Train Accuracy: 0.2824, Val Loss: 1.6021, Val Accuracy: 0.2946
Epoch 503/10000, Train Loss: 1.6018, Train Accuracy: 0.2801, Val Loss: 1.6020, Val Accuracy: 0.2991
Epoch 504/10000, Train Loss: 1.6022, Train Accuracy: 0.2902, Val Loss: 1.6020, Val Accuracy: 0.2991
Epoch 505/10000, Train Loss: 1.6016, Train Accuracy: 0.3013, Val Loss: 1.6020, Val Accuracy: 0.2991
Epoch 506/10000, Train Loss: 1.6013, Train Accuracy: 0.3025, Val Loss: 1.6020, Val Accuracy: 0.2991
Epoch 507/10000, Train Loss: 1.6017, Train Accuracy: 0.2891, Val Loss: 1.6020, Val Accuracy: 0.2991
Epoch 508/10000, Train Loss: 1.6004, Train Accuracy: 0.3114, Val Loss: 1.6019, Val Accuracy: 0.2991
Epoch 509/10000, Train Loss: 1.6009, Train Accuracy: 0.2868, Val Loss: 1.6019, Val Accuracy: 0.2991
Epoch 510/10000, Train Loss: 1.6015, Train Accuracy: 0.2868, Val Loss: 1.6019, Val Accuracy: 0.2991

Epoch 511/10000, Train Loss: 1.6012, Train Accuracy: 0.2935, Val Loss: 1.6019, Val Accuracy: 0.2991
Epoch 512/10000, Train Loss: 1.6016, Train Accuracy: 0.2801, Val Loss: 1.6019, Val Accuracy: 0.2991
Epoch 513/10000, Train Loss: 1.6026, Train Accuracy: 0.2790, Val Loss: 1.6018, Val Accuracy: 0.2991
Epoch 514/10000, Train Loss: 1.6007, Train Accuracy: 0.2835, Val Loss: 1.6018, Val Accuracy: 0.2991
Epoch 515/10000, Train Loss: 1.6018, Train Accuracy: 0.2812, Val Loss: 1.6018, Val Accuracy: 0.2991
Epoch 516/10000, Train Loss: 1.6011, Train Accuracy: 0.2779, Val Loss: 1.6018, Val Accuracy: 0.2991
Epoch 517/10000, Train Loss: 1.6014, Train Accuracy: 0.2980, Val Loss: 1.6018, Val Accuracy: 0.2991
Epoch 518/10000, Train Loss: 1.6001, Train Accuracy: 0.3002, Val Loss: 1.6017, Val Accuracy: 0.2991
Epoch 519/10000, Train Loss: 1.6017, Train Accuracy: 0.2857, Val Loss: 1.6017, Val Accuracy: 0.2991
Epoch 520/10000, Train Loss: 1.6021, Train Accuracy: 0.2924, Val Loss: 1.6017, Val Accuracy: 0.2991
Epoch 521/10000, Train Loss: 1.6006, Train Accuracy: 0.3069, Val Loss: 1.6017, Val Accuracy: 0.2991
Epoch 522/10000, Train Loss: 1.6006, Train Accuracy: 0.3036, Val Loss: 1.6016, Val Accuracy: 0.2991
Epoch 523/10000, Train Loss: 1.6010, Train Accuracy: 0.2980, Val Loss: 1.6016, Val Accuracy: 0.2991
Epoch 524/10000, Train Loss: 1.6013, Train Accuracy: 0.2846, Val Loss: 1.6016, Val Accuracy: 0.2991
Epoch 525/10000, Train Loss: 1.6013, Train Accuracy: 0.2879, Val Loss: 1.6016, Val Accuracy: 0.2991
Epoch 526/10000, Train Loss: 1.6007, Train Accuracy: 0.3025, Val Loss: 1.6016, Val Accuracy: 0.2991
Epoch 527/10000, Train Loss: 1.6005, Train Accuracy: 0.3025, Val Loss: 1.6015, Val Accuracy: 0.2991
Epoch 528/10000, Train Loss: 1.6014, Train Accuracy: 0.3058, Val Loss: 1.6015, Val Accuracy: 0.2991
Epoch 529/10000, Train Loss: 1.6012, Train Accuracy: 0.2935, Val Loss: 1.6015, Val Accuracy: 0.2991
Epoch 530/10000, Train Loss: 1.5994, Train Accuracy: 0.3058, Val Loss: 1.6015, Val Accuracy: 0.2991
Epoch 531/10000, Train Loss: 1.6006, Train Accuracy: 0.3013, Val Loss: 1.6015, Val Accuracy: 0.2991
Epoch 532/10000, Train Loss: 1.5997, Train Accuracy: 0.2913, Val Loss: 1.6014, Val Accuracy: 0.2991
Epoch 533/10000, Train Loss: 1.6003, Train Accuracy: 0.3025, Val Loss: 1.6014, Val Accuracy: 0.2991
Epoch 534/10000, Train Loss: 1.6010, Train Accuracy: 0.2946, Val Loss: 1.6014, Val Accuracy: 0.2991
Epoch 535/10000, Train Loss: 1.6007, Train Accuracy: 0.2879, Val Loss: 1.6014, Val Accuracy: 0.3036
Epoch 536/10000, Train Loss: 1.6003, Train Accuracy: 0.2924, Val Loss: 1.6014, Val Accuracy: 0.3036
Epoch 537/10000, Train Loss: 1.6006, Train Accuracy: 0.2913, Val Loss: 1.6013, Val Accuracy: 0.3036
Epoch 538/10000, Train Loss: 1.6000, Train Accuracy: 0.3136, Val Loss: 1.6013, Val Accuracy: 0.3036
Epoch 539/10000, Train Loss: 1.6013, Train Accuracy: 0.2924, Val Loss: 1.6013, Val Accuracy: 0.3036
Epoch 540/10000, Train Loss: 1.5998, Train Accuracy: 0.3203, Val Loss: 1.6013, Val Accuracy: 0.3036
Epoch 541/10000, Train Loss: 1.6009, Train Accuracy: 0.3036, Val Loss: 1.6013, Val Accuracy: 0.3036
Epoch 542/10000, Train Loss: 1.5996, Train Accuracy: 0.3036, Val Loss: 1.6012, Val Accuracy: 0.3036
Epoch 543/10000, Train Loss: 1.5995, Train Accuracy: 0.2946, Val Loss: 1.6012, Val Accuracy: 0.3036
Epoch 544/10000, Train Loss: 1.5990, Train Accuracy: 0.3214, Val Loss: 1.6012, Val Accuracy: 0.3036
Epoch 545/10000, Train Loss: 1.6017, Train Accuracy: 0.2835, Val Loss: 1.6012, Val Accuracy: 0.3036
Epoch 546/10000, Train Loss: 1.6001, Train Accuracy: 0.3047, Val Loss: 1.6011, Val Accuracy: 0.2991
Epoch 547/10000, Train Loss: 1.5985, Train Accuracy: 0.3080, Val Loss: 1.6011, Val Accuracy: 0.3080
Epoch 548/10000, Train Loss: 1.6005, Train Accuracy: 0.3092, Val Loss: 1.6011, Val Accuracy: 0.3125
Epoch 549/10000, Train Loss: 1.6000, Train Accuracy: 0.2924, Val Loss: 1.6011, Val Accuracy: 0.3080
Epoch 550/10000, Train Loss: 1.6009, Train Accuracy: 0.2779, Val Loss: 1.6010, Val Accuracy: 0.3125
Epoch 551/10000, Train Loss: 1.6006, Train Accuracy: 0.3136, Val Loss: 1.6010, Val Accuracy: 0.3125
Epoch 552/10000, Train Loss: 1.6013, Train Accuracy: 0.2913, Val Loss: 1.6010, Val Accuracy: 0.3125
Epoch 553/10000, Train Loss: 1.6003, Train Accuracy: 0.2969, Val Loss: 1.6010, Val Accuracy: 0.3125
Epoch 554/10000, Train Loss: 1.6005, Train Accuracy: 0.3013, Val Loss: 1.6010, Val Accuracy: 0.3125
Epoch 555/10000, Train Loss: 1.6002, Train Accuracy: 0.3047, Val Loss: 1.6009, Val Accuracy: 0.3125
Epoch 556/10000, Train Loss: 1.5997, Train Accuracy: 0.3147, Val Loss: 1.6009, Val Accuracy: 0.3125
Epoch 557/10000, Train Loss: 1.5993, Train Accuracy: 0.3125, Val Loss: 1.6009, Val Accuracy: 0.3125
Epoch 558/10000, Train Loss: 1.6007, Train Accuracy: 0.2924, Val Loss: 1.6009, Val Accuracy: 0.3170
Epoch 559/10000, Train Loss: 1.6000, Train Accuracy: 0.2980, Val Loss: 1.6008, Val Accuracy: 0.3170
Epoch 560/10000, Train Loss: 1.6016, Train Accuracy: 0.2746, Val Loss: 1.6008, Val Accuracy: 0.3214
Epoch 561/10000, Train Loss: 1.6008, Train Accuracy: 0.2857, Val Loss: 1.6008, Val Accuracy: 0.3214
Epoch 562/10000, Train Loss: 1.5998, Train Accuracy: 0.3125, Val Loss: 1.6008, Val Accuracy: 0.3214
Epoch 563/10000, Train Loss: 1.6006, Train Accuracy: 0.2902, Val Loss: 1.6008, Val Accuracy: 0.3214
Epoch 564/10000, Train Loss: 1.6006, Train Accuracy: 0.2879, Val Loss: 1.6007, Val Accuracy: 0.3214
Epoch 565/10000, Train Loss: 1.6002, Train Accuracy: 0.3136, Val Loss: 1.6007, Val Accuracy: 0.3259
Epoch 566/10000, Train Loss: 1.5990, Train Accuracy: 0.3114, Val Loss: 1.6007, Val Accuracy: 0.3259
Epoch 567/10000, Train Loss: 1.6008, Train Accuracy: 0.2969, Val Loss: 1.6007, Val Accuracy: 0.3259
Epoch 568/10000, Train Loss: 1.5992, Train Accuracy: 0.3214, Val Loss: 1.6006, Val Accuracy: 0.3259
Epoch 569/10000, Train Loss: 1.6004, Train Accuracy: 0.2935, Val Loss: 1.6006, Val Accuracy: 0.3259
Epoch 570/10000, Train Loss: 1.5999, Train Accuracy: 0.3069, Val Loss: 1.6006, Val Accuracy: 0.3259
Epoch 571/10000, Train Loss: 1.5977, Train Accuracy: 0.3292, Val Loss: 1.6005, Val Accuracy: 0.3304
Epoch 572/10000, Train Loss: 1.5992, Train Accuracy: 0.3103, Val Loss: 1.6005, Val Accuracy: 0.3304
Epoch 573/10000, Train Loss: 1.5999, Train Accuracy: 0.2958, Val Loss: 1.6005, Val Accuracy: 0.3348
Epoch 574/10000, Train Loss: 1.5994, Train Accuracy: 0.2958, Val Loss: 1.6005, Val Accuracy: 0.3348
Epoch 575/10000, Train Loss: 1.5988, Train Accuracy: 0.3092, Val Loss: 1.6005, Val Accuracy: 0.3348
Epoch 576/10000, Train Loss: 1.5997, Train Accuracy: 0.2868, Val Loss: 1.6004, Val Accuracy: 0.3393
Epoch 577/10000, Train Loss: 1.5991, Train Accuracy: 0.2790, Val Loss: 1.6004, Val Accuracy: 0.3438
Epoch 578/10000, Train Loss: 1.5997, Train Accuracy: 0.3214, Val Loss: 1.6004, Val Accuracy: 0.3438
Epoch 579/10000, Train Loss: 1.5992, Train Accuracy: 0.3181, Val Loss: 1.6004, Val Accuracy: 0.3438
Epoch 580/10000, Train Loss: 1.6006, Train Accuracy: 0.3002, Val Loss: 1.6003, Val Accuracy: 0.3438
Epoch 581/10000, Train Loss: 1.5988, Train Accuracy: 0.3125, Val Loss: 1.6003, Val Accuracy: 0.3482
Epoch 582/10000, Train Loss: 1.5989, Train Accuracy: 0.2991, Val Loss: 1.6003, Val Accuracy: 0.3482
Epoch 583/10000, Train Loss: 1.6003, Train Accuracy: 0.2924, Val Loss: 1.6003, Val Accuracy: 0.3482
Epoch 584/10000, Train Loss: 1.5991, Train Accuracy: 0.2969, Val Loss: 1.6002, Val Accuracy: 0.3482
Epoch 585/10000, Train Loss: 1.5993, Train Accuracy: 0.3080, Val Loss: 1.6002, Val Accuracy: 0.3482
Epoch 586/10000, Train Loss: 1.5990, Train Accuracy: 0.3326, Val Loss: 1.6002, Val Accuracy: 0.3482
Epoch 587/10000, Train Loss: 1.6014, Train Accuracy: 0.2812, Val Loss: 1.6001, Val Accuracy: 0.3482
Epoch 588/10000, Train Loss: 1.6000, Train Accuracy: 0.3114, Val Loss: 1.6001, Val Accuracy: 0.3527
Epoch 589/10000, Train Loss: 1.6004, Train Accuracy: 0.2846, Val Loss: 1.6001, Val Accuracy: 0.3527
Epoch 590/10000, Train Loss: 1.5988, Train Accuracy: 0.3136, Val Loss: 1.6001, Val Accuracy: 0.3527
Epoch 591/10000, Train Loss: 1.6001, Train Accuracy: 0.3002, Val Loss: 1.6001, Val Accuracy: 0.3571
Epoch 592/10000, Train Loss: 1.5990, Train Accuracy: 0.3181, Val Loss: 1.6000, Val Accuracy: 0.3571
Epoch 593/10000, Train Loss: 1.5992, Train Accuracy: 0.3103, Val Loss: 1.6000, Val Accuracy: 0.3571
Epoch 594/10000, Train Loss: 1.6001, Train Accuracy: 0.3103, Val Loss: 1.6000, Val Accuracy: 0.3571
Epoch 595/10000, Train Loss: 1.5981, Train Accuracy: 0.3147, Val Loss: 1.6000, Val Accuracy: 0.3571
Epoch 596/10000, Train Loss: 1.5989, Train Accuracy: 0.3147, Val Loss: 1.5999, Val Accuracy: 0.3571
Epoch 597/10000, Train Loss: 1.5988, Train Accuracy: 0.2946, Val Loss: 1.5999, Val Accuracy: 0.3571
Epoch 598/10000, Train Loss: 1.5996, Train Accuracy: 0.3225, Val Loss: 1.5999, Val Accuracy: 0.3571
Epoch 599/10000, Train Loss: 1.5975, Train Accuracy: 0.3248, Val Loss: 1.5999, Val Accuracy: 0.3571
Epoch 600/10000, Train Loss: 1.5987, Train Accuracy: 0.3270, Val Loss: 1.5999, Val Accuracy: 0.3571
Epoch 601/10000, Train Loss: 1.5983, Train Accuracy: 0.3203, Val Loss: 1.5998, Val Accuracy: 0.3571
Epoch 602/10000, Train Loss: 1.5985, Train Accuracy: 0.3181, Val Loss: 1.5998, Val Accuracy: 0.3571
Epoch 603/10000, Train Loss: 1.5996, Train Accuracy: 0.3092, Val Loss: 1.5998, Val Accuracy: 0.3571
Epoch 604/10000, Train Loss: 1.5988, Train Accuracy: 0.3225, Val Loss: 1.5998, Val Accuracy: 0.3616
Epoch 605/10000, Train Loss: 1.5983, Train Accuracy: 0.3025, Val Loss: 1.5998, Val Accuracy: 0.3616
Epoch 606/10000, Train Loss: 1.5985, Train Accuracy: 0.2980, Val Loss: 1.5997, Val Accuracy: 0.3616
Epoch 607/10000, Train Loss: 1.5994, Train Accuracy: 0.3170, Val Loss: 1.5997, Val Accuracy: 0.3571
Epoch 608/10000, Train Loss: 1.5982, Train Accuracy: 0.3170, Val Loss: 1.5997, Val Accuracy: 0.3616
Epoch 609/10000, Train Loss: 1.5987, Train Accuracy: 0.2946, Val Loss: 1.5997, Val Accuracy: 0.3616
Epoch 610/10000, Train Loss: 1.5994, Train Accuracy: 0.3147, Val Loss: 1.5996, Val Accuracy: 0.3616
Epoch 611/10000, Train Loss: 1.5978, Train Accuracy: 0.3292, Val Loss: 1.5996, Val Accuracy: 0.3616
Epoch 612/10000, Train Loss: 1.5978, Train Accuracy: 0.3147, Val Loss: 1.5996, Val Accuracy: 0.3616
Epoch 613/10000, Train Loss: 1.5991, Train Accuracy: 0.3103, Val Loss: 1.5996, Val Accuracy: 0.3616
Epoch 614/10000, Train Loss: 1.5995, Train Accuracy: 0.2935, Val Loss: 1.5996, Val Accuracy: 0.3616
Epoch 615/10000, Train Loss: 1.5978, Train Accuracy: 0.3292, Val Loss: 1.5995, Val Accuracy: 0.3616
Epoch 616/10000, Train Loss: 1.5989, Train Accuracy: 0.3170, Val Loss: 1.5995, Val Accuracy: 0.3616
Epoch 617/10000, Train Loss: 1.5982, Train Accuracy: 0.3136, Val Loss: 1.5995, Val Accuracy: 0.3616
Epoch 618/10000, Train Loss: 1.5999, Train Accuracy: 0.3147, Val Loss: 1.5995, Val Accuracy: 0.3705
Epoch 619/10000, Train Loss: 1.5985, Train Accuracy: 0.3136, Val Loss: 1.5994, Val Accuracy: 0.3705
Epoch 620/10000, Train Loss: 1.5982, Train Accuracy: 0.2991, Val Loss: 1.5994, Val Accuracy: 0.3705
Epoch 621/10000, Train Loss: 1.5977, Train Accuracy: 0.3225, Val Loss: 1.5994, Val Accuracy: 0.3705
Epoch 622/10000, Train Loss: 1.5977, Train Accuracy: 0.3103, Val Loss: 1.5993, Val Accuracy: 0.3705
Epoch 623/10000, Train Loss: 1.5974, Train Accuracy: 0.3170, Val Loss: 1.5993, Val Accuracy: 0.3705
Epoch 624/10000, Train Loss: 1.5978, Train Accuracy: 0.3203, Val Loss: 1.5993, Val Accuracy: 0.3705
Epoch 625/10000, Train Loss: 1.5968, Train Accuracy: 0.3225, Val Loss: 1.5993, Val Accuracy: 0.3750
Epoch 626/10000, Train Loss: 1.5973, Train Accuracy: 0.3225, Val Loss: 1.5992, Val Accuracy: 0.3750
Epoch 627/10000, Train Loss: 1.5978, Train Accuracy: 0.3092, Val Loss: 1.5992, Val Accuracy: 0.3750
Epoch 628/10000, Train Loss: 1.5976, Train Accuracy: 0.3248, Val Loss: 1.5992, Val Accuracy: 0.3795
Epoch 629/10000, Train Loss: 1.5980, Train Accuracy: 0.3158, Val Loss: 1.5992, Val Accuracy: 0.3795
Epoch 630/10000, Train Loss: 1.5988, Train Accuracy: 0.3080, Val Loss: 1.5991, Val Accuracy: 0.3750
Epoch 631/10000, Train Loss: 1.5976, Train Accuracy: 0.3103, Val Loss: 1.5991, Val Accuracy: 0.3795
Epoch 632/10000, Train Loss: 1.5984, Train Accuracy: 0.2980, Val Loss: 1.5991, Val Accuracy: 0.3795
Epoch 633/10000, Train Loss: 1.5986, Train Accuracy: 0.2958, Val Loss: 1.5990, Val Accuracy: 0.3795
Epoch 634/10000, Train Loss: 1.5983, Train Accuracy: 0.3047, Val Loss: 1.5990, Val Accuracy: 0.3795
Epoch 635/10000, Train Loss: 1.5985, Train Accuracy: 0.3125, Val Loss: 1.5990, Val Accuracy: 0.3795
Epoch 636/10000, Train Loss: 1.5983, Train Accuracy: 0.3047, Val Loss: 1.5990, Val Accuracy: 0.3795
Epoch 637/10000, Train Loss: 1.5978, Train Accuracy: 0.3147, Val Loss: 1.5989, Val Accuracy: 0.3795
Epoch 638/10000, Train Loss: 1.5988, Train Accuracy: 0.3214, Val Loss: 1.5989, Val Accuracy: 0.3795
Epoch 639/10000, Train Loss: 1.5977, Train Accuracy: 0.3281, Val Loss: 1.5989, Val Accuracy: 0.3795
Epoch 640/10000, Train Loss: 1.5965, Train Accuracy: 0.3415, Val Loss: 1.5988, Val Accuracy: 0.3795
Epoch 641/10000, Train Loss: 1.5981, Train Accuracy: 0.3069, Val Loss: 1.5988, Val Accuracy: 0.3795
Epoch 642/10000, Train Loss: 1.5968, Train Accuracy: 0.3237, Val Loss: 1.5988, Val Accuracy: 0.3795
Epoch 643/10000, Train Loss: 1.5983, Train Accuracy: 0.3158, Val Loss: 1.5988, Val Accuracy: 0.3795
Epoch 644/10000, Train Loss: 1.5970, Train Accuracy: 0.3125, Val Loss: 1.5988, Val Accuracy: 0.3795
Epoch 645/10000, Train Loss: 1.5988, Train Accuracy: 0.2969, Val Loss: 1.5987, Val Accuracy: 0.3795
Epoch 646/10000, Train Loss: 1.6002, Train Accuracy: 0.3103, Val Loss: 1.5987, Val Accuracy: 0.3795
Epoch 647/10000, Train Loss: 1.5980, Train Accuracy: 0.3069, Val Loss: 1.5987, Val Accuracy: 0.3795
Epoch 648/10000, Train Loss: 1.5974, Train Accuracy: 0.3114, Val Loss: 1.5986, Val Accuracy: 0.3795
Epoch 649/10000, Train Loss: 1.5977, Train Accuracy: 0.3237, Val Loss: 1.5986, Val Accuracy: 0.3795
Epoch 650/10000, Train Loss: 1.5966, Train Accuracy: 0.3382, Val Loss: 1.5986, Val Accuracy: 0.3795
Epoch 651/10000, Train Loss: 1.5972, Train Accuracy: 0.3404, Val Loss: 1.5986, Val Accuracy: 0.3795
Epoch 652/10000, Train Loss: 1.5964, Train Accuracy: 0.3315, Val Loss: 1.5985, Val Accuracy: 0.3795
Epoch 653/10000, Train Loss: 1.5991, Train Accuracy: 0.2868, Val Loss: 1.5985, Val Accuracy: 0.3795
Epoch 654/10000, Train Loss: 1.5972, Train Accuracy: 0.3382, Val Loss: 1.5985, Val Accuracy: 0.3795
Epoch 655/10000, Train Loss: 1.5967, Train Accuracy: 0.3270, Val Loss: 1.5985, Val Accuracy: 0.3795
Epoch 656/10000, Train Loss: 1.5978, Train Accuracy: 0.3170, Val Loss: 1.5984, Val Accuracy: 0.3795
Epoch 657/10000, Train Loss: 1.5981, Train Accuracy: 0.3125, Val Loss: 1.5984, Val Accuracy: 0.3795
Epoch 658/10000, Train Loss: 1.5978, Train Accuracy: 0.3080, Val Loss: 1.5984, Val Accuracy: 0.3795
Epoch 659/10000, Train Loss: 1.5966, Train Accuracy: 0.3203, Val Loss: 1.5984, Val Accuracy: 0.3795
Epoch 660/10000, Train Loss: 1.5977, Train Accuracy: 0.3158, Val Loss: 1.5983, Val Accuracy: 0.3795
Epoch 661/10000, Train Loss: 1.5972, Train Accuracy: 0.3270, Val Loss: 1.5983, Val Accuracy: 0.3795
Epoch 662/10000, Train Loss: 1.5970, Train Accuracy: 0.3136, Val Loss: 1.5983, Val Accuracy: 0.3795
Epoch 663/10000, Train Loss: 1.5975, Train Accuracy: 0.3214, Val Loss: 1.5982, Val Accuracy: 0.3795
Epoch 664/10000, Train Loss: 1.5978, Train Accuracy: 0.3192, Val Loss: 1.5982, Val Accuracy: 0.3795
Epoch 665/10000, Train Loss: 1.5967, Train Accuracy: 0.3192, Val Loss: 1.5982, Val Accuracy: 0.3795
Epoch 666/10000, Train Loss: 1.5979, Train Accuracy: 0.3225, Val Loss: 1.5982, Val Accuracy: 0.3795
Epoch 667/10000, Train Loss: 1.5960, Train Accuracy: 0.3315, Val Loss: 1.5981, Val Accuracy: 0.3795
Epoch 668/10000, Train Loss: 1.5962, Train Accuracy: 0.3315, Val Loss: 1.5981, Val Accuracy: 0.3839
Epoch 669/10000, Train Loss: 1.5970, Train Accuracy: 0.3281, Val Loss: 1.5981, Val Accuracy: 0.3929
Epoch 670/10000, Train Loss: 1.5964, Train Accuracy: 0.3359, Val Loss: 1.5980, Val Accuracy: 0.3929
Epoch 671/10000, Train Loss: 1.5979, Train Accuracy: 0.3025, Val Loss: 1.5980, Val Accuracy: 0.3929
Epoch 672/10000, Train Loss: 1.5955, Train Accuracy: 0.3460, Val Loss: 1.5980, Val Accuracy: 0.3929
Epoch 673/10000, Train Loss: 1.5970, Train Accuracy: 0.3326, Val Loss: 1.5980, Val Accuracy: 0.3929
Epoch 674/10000, Train Loss: 1.5968, Train Accuracy: 0.3170, Val Loss: 1.5979, Val Accuracy: 0.3929
Epoch 675/10000, Train Loss: 1.5979, Train Accuracy: 0.3114, Val Loss: 1.5979, Val Accuracy: 0.3973
Epoch 676/10000, Train Loss: 1.5969, Train Accuracy: 0.3292, Val Loss: 1.5979, Val Accuracy: 0.3884
Epoch 677/10000, Train Loss: 1.5948, Train Accuracy: 0.3493, Val Loss: 1.5978, Val Accuracy: 0.3884
Epoch 678/10000, Train Loss: 1.5967, Train Accuracy: 0.3371, Val Loss: 1.5978, Val Accuracy: 0.3884
Epoch 679/10000, Train Loss: 1.5961, Train Accuracy: 0.3404, Val Loss: 1.5978, Val Accuracy: 0.3884
Epoch 680/10000, Train Loss: 1.5955, Train Accuracy: 0.3315, Val Loss: 1.5977, Val Accuracy: 0.3884
Epoch 681/10000, Train Loss: 1.5972, Train Accuracy: 0.3214, Val Loss: 1.5977, Val Accuracy: 0.3884
Epoch 682/10000, Train Loss: 1.5957, Train Accuracy: 0.3270, Val Loss: 1.5977, Val Accuracy: 0.3884
Epoch 683/10000, Train Loss: 1.5960, Train Accuracy: 0.3259, Val Loss: 1.5977, Val Accuracy: 0.3884
Epoch 684/10000, Train Loss: 1.5960, Train Accuracy: 0.3292, Val Loss: 1.5976, Val Accuracy: 0.3929
Epoch 685/10000, Train Loss: 1.5973, Train Accuracy: 0.3147, Val Loss: 1.5976, Val Accuracy: 0.3929
Epoch 686/10000, Train Loss: 1.5977, Train Accuracy: 0.3069, Val Loss: 1.5976, Val Accuracy: 0.3929
Epoch 687/10000, Train Loss: 1.5966, Train Accuracy: 0.3248, Val Loss: 1.5976, Val Accuracy: 0.3929
Epoch 688/10000, Train Loss: 1.5961, Train Accuracy: 0.3270, Val Loss: 1.5975, Val Accuracy: 0.3929
Epoch 689/10000, Train Loss: 1.5967, Train Accuracy: 0.3214, Val Loss: 1.5975, Val Accuracy: 0.3929
Epoch 690/10000, Train Loss: 1.5957, Train Accuracy: 0.3025, Val Loss: 1.5975, Val Accuracy: 0.3929
Epoch 691/10000, Train Loss: 1.5974, Train Accuracy: 0.3069, Val Loss: 1.5974, Val Accuracy: 0.3929
Epoch 692/10000, Train Loss: 1.5967, Train Accuracy: 0.3214, Val Loss: 1.5974, Val Accuracy: 0.3929
Epoch 693/10000, Train Loss: 1.5965, Train Accuracy: 0.3125, Val Loss: 1.5974, Val Accuracy: 0.3929
Epoch 694/10000, Train Loss: 1.5960, Train Accuracy: 0.3538, Val Loss: 1.5974, Val Accuracy: 0.3929
Epoch 695/10000, Train Loss: 1.5963, Train Accuracy: 0.3270, Val Loss: 1.5973, Val Accuracy: 0.3929
Epoch 696/10000, Train Loss: 1.5964, Train Accuracy: 0.3281, Val Loss: 1.5973, Val Accuracy: 0.3929
Epoch 697/10000, Train Loss: 1.5950, Train Accuracy: 0.3415, Val Loss: 1.5973, Val Accuracy: 0.3929
Epoch 698/10000, Train Loss: 1.5957, Train Accuracy: 0.3348, Val Loss: 1.5973, Val Accuracy: 0.3929
Epoch 699/10000, Train Loss: 1.5953, Train Accuracy: 0.3371, Val Loss: 1.5972, Val Accuracy: 0.3929
Epoch 700/10000, Train Loss: 1.5957, Train Accuracy: 0.3136, Val Loss: 1.5972, Val Accuracy: 0.3929
Epoch 701/10000, Train Loss: 1.5959, Train Accuracy: 0.3404, Val Loss: 1.5972, Val Accuracy: 0.3929
Epoch 702/10000, Train Loss: 1.5963, Train Accuracy: 0.3438, Val Loss: 1.5971, Val Accuracy: 0.3929
Epoch 703/10000, Train Loss: 1.5950, Train Accuracy: 0.3326, Val Loss: 1.5971, Val Accuracy: 0.3929
Epoch 704/10000, Train Loss: 1.5955, Train Accuracy: 0.3371, Val Loss: 1.5971, Val Accuracy: 0.3929
Epoch 705/10000, Train Loss: 1.5967, Train Accuracy: 0.3337, Val Loss: 1.5971, Val Accuracy: 0.3929
Epoch 706/10000, Train Loss: 1.5965, Train Accuracy: 0.3214, Val Loss: 1.5970, Val Accuracy: 0.3929
Epoch 707/10000, Train Loss: 1.5953, Train Accuracy: 0.3348, Val Loss: 1.5970, Val Accuracy: 0.3929
Epoch 708/10000, Train Loss: 1.5971, Train Accuracy: 0.3259, Val Loss: 1.5970, Val Accuracy: 0.3929
Epoch 709/10000, Train Loss: 1.5957, Train Accuracy: 0.3404, Val Loss: 1.5970, Val Accuracy: 0.3929
Epoch 710/10000, Train Loss: 1.5952, Train Accuracy: 0.3214, Val Loss: 1.5969, Val Accuracy: 0.3929
Epoch 711/10000, Train Loss: 1.5955, Train Accuracy: 0.3248, Val Loss: 1.5969, Val Accuracy: 0.3929
Epoch 712/10000, Train Loss: 1.5961, Train Accuracy: 0.3214, Val Loss: 1.5969, Val Accuracy: 0.3929
Epoch 713/10000, Train Loss: 1.5953, Train Accuracy: 0.3371, Val Loss: 1.5968, Val Accuracy: 0.3929
Epoch 714/10000, Train Loss: 1.5951, Train Accuracy: 0.3460, Val Loss: 1.5968, Val Accuracy: 0.3929
Epoch 715/10000, Train Loss: 1.5959, Train Accuracy: 0.3348, Val Loss: 1.5968, Val Accuracy: 0.3929
Epoch 716/10000, Train Loss: 1.5957, Train Accuracy: 0.3326, Val Loss: 1.5967, Val Accuracy: 0.3929
Epoch 717/10000, Train Loss: 1.5965, Train Accuracy: 0.3114, Val Loss: 1.5967, Val Accuracy: 0.3929
Epoch 718/10000, Train Loss: 1.5958, Train Accuracy: 0.3158, Val Loss: 1.5967, Val Accuracy: 0.3929
Epoch 719/10000, Train Loss: 1.5961, Train Accuracy: 0.3158, Val Loss: 1.5966, Val Accuracy: 0.3929
Epoch 720/10000, Train Loss: 1.5961, Train Accuracy: 0.3192, Val Loss: 1.5966, Val Accuracy: 0.3929
Epoch 721/10000, Train Loss: 1.5957, Train Accuracy: 0.3348, Val Loss: 1.5966, Val Accuracy: 0.3929
Epoch 722/10000, Train Loss: 1.5944, Train Accuracy: 0.3460, Val Loss: 1.5965, Val Accuracy: 0.3929
Epoch 723/10000, Train Loss: 1.5968, Train Accuracy: 0.3348, Val Loss: 1.5965, Val Accuracy: 0.3929
Epoch 724/10000, Train Loss: 1.5951, Train Accuracy: 0.3493, Val Loss: 1.5965, Val Accuracy: 0.3929
Epoch 725/10000, Train Loss: 1.5958, Train Accuracy: 0.3225, Val Loss: 1.5965, Val Accuracy: 0.3929
Epoch 726/10000, Train Loss: 1.5960, Train Accuracy: 0.2991, Val Loss: 1.5964, Val Accuracy: 0.3929
Epoch 727/10000, Train Loss: 1.5951, Train Accuracy: 0.3415, Val Loss: 1.5964, Val Accuracy: 0.3929
Epoch 728/10000, Train Loss: 1.5952, Train Accuracy: 0.3504, Val Loss: 1.5964, Val Accuracy: 0.3929
Epoch 729/10000, Train Loss: 1.5955, Train Accuracy: 0.3359, Val Loss: 1.5963, Val Accuracy: 0.3929
Epoch 730/10000, Train Loss: 1.5932, Train Accuracy: 0.3426, Val Loss: 1.5963, Val Accuracy: 0.3929
Epoch 731/10000, Train Loss: 1.5945, Train Accuracy: 0.3225, Val Loss: 1.5963, Val Accuracy: 0.3929
Epoch 732/10000, Train Loss: 1.5947, Train Accuracy: 0.3583, Val Loss: 1.5962, Val Accuracy: 0.3929
Epoch 733/10000, Train Loss: 1.5956, Train Accuracy: 0.3315, Val Loss: 1.5962, Val Accuracy: 0.3929
Epoch 734/10000, Train Loss: 1.5941, Train Accuracy: 0.3337, Val Loss: 1.5962, Val Accuracy: 0.3929
Epoch 735/10000, Train Loss: 1.5954, Train Accuracy: 0.3259, Val Loss: 1.5961, Val Accuracy: 0.3929
Epoch 736/10000, Train Loss: 1.5967, Train Accuracy: 0.3092, Val Loss: 1.5961, Val Accuracy: 0.3929
Epoch 737/10000, Train Loss: 1.5952, Train Accuracy: 0.3259, Val Loss: 1.5961, Val Accuracy: 0.3929
Epoch 738/10000, Train Loss: 1.5957, Train Accuracy: 0.3147, Val Loss: 1.5961, Val Accuracy: 0.3929
Epoch 739/10000, Train Loss: 1.5953, Train Accuracy: 0.3371, Val Loss: 1.5961, Val Accuracy: 0.3929
Epoch 740/10000, Train Loss: 1.5935, Train Accuracy: 0.3426, Val Loss: 1.5960, Val Accuracy: 0.3929
Epoch 741/10000, Train Loss: 1.5949, Train Accuracy: 0.3516, Val Loss: 1.5960, Val Accuracy: 0.3929
Epoch 742/10000, Train Loss: 1.5964, Train Accuracy: 0.3237, Val Loss: 1.5960, Val Accuracy: 0.3929
Epoch 743/10000, Train Loss: 1.5952, Train Accuracy: 0.3337, Val Loss: 1.5959, Val Accuracy: 0.3929
Epoch 744/10000, Train Loss: 1.5941, Train Accuracy: 0.3415, Val Loss: 1.5959, Val Accuracy: 0.3929
Epoch 745/10000, Train Loss: 1.5941, Train Accuracy: 0.3493, Val Loss: 1.5959, Val Accuracy: 0.3929
Epoch 746/10000, Train Loss: 1.5957, Train Accuracy: 0.3270, Val Loss: 1.5959, Val Accuracy: 0.3929
Epoch 747/10000, Train Loss: 1.5941, Train Accuracy: 0.3438, Val Loss: 1.5958, Val Accuracy: 0.3929
Epoch 748/10000, Train Loss: 1.5954, Train Accuracy: 0.3426, Val Loss: 1.5958, Val Accuracy: 0.3929
Epoch 749/10000, Train Loss: 1.5934, Train Accuracy: 0.3393, Val Loss: 1.5957, Val Accuracy: 0.3929
Epoch 750/10000, Train Loss: 1.5933, Train Accuracy: 0.3482, Val Loss: 1.5957, Val Accuracy: 0.3929
Epoch 751/10000, Train Loss: 1.5949, Train Accuracy: 0.3348, Val Loss: 1.5957, Val Accuracy: 0.3929
Epoch 752/10000, Train Loss: 1.5944, Train Accuracy: 0.3270, Val Loss: 1.5956, Val Accuracy: 0.3929
Epoch 753/10000, Train Loss: 1.5942, Train Accuracy: 0.3337, Val Loss: 1.5956, Val Accuracy: 0.3929
Epoch 754/10000, Train Loss: 1.5945, Train Accuracy: 0.3237, Val Loss: 1.5956, Val Accuracy: 0.3929
Epoch 755/10000, Train Loss: 1.5951, Train Accuracy: 0.3337, Val Loss: 1.5955, Val Accuracy: 0.3929
Epoch 756/10000, Train Loss: 1.5934, Train Accuracy: 0.3449, Val Loss: 1.5955, Val Accuracy: 0.3929
Epoch 757/10000, Train Loss: 1.5931, Train Accuracy: 0.3426, Val Loss: 1.5954, Val Accuracy: 0.3929
Epoch 758/10000, Train Loss: 1.5955, Train Accuracy: 0.3225, Val Loss: 1.5954, Val Accuracy: 0.3929
Epoch 759/10000, Train Loss: 1.5929, Train Accuracy: 0.3359, Val Loss: 1.5954, Val Accuracy: 0.3929
Epoch 760/10000, Train Loss: 1.5928, Train Accuracy: 0.3359, Val Loss: 1.5953, Val Accuracy: 0.3929
Epoch 761/10000, Train Loss: 1.5940, Train Accuracy: 0.3638, Val Loss: 1.5953, Val Accuracy: 0.3929
Epoch 762/10000, Train Loss: 1.5934, Train Accuracy: 0.3281, Val Loss: 1.5953, Val Accuracy: 0.3884
Epoch 763/10000, Train Loss: 1.5940, Train Accuracy: 0.3415, Val Loss: 1.5953, Val Accuracy: 0.3929
Epoch 764/10000, Train Loss: 1.5942, Train Accuracy: 0.3292, Val Loss: 1.5952, Val Accuracy: 0.3929
Epoch 765/10000, Train Loss: 1.5940, Train Accuracy: 0.3460, Val Loss: 1.5952, Val Accuracy: 0.3884
Epoch 766/10000, Train Loss: 1.5944, Train Accuracy: 0.3248, Val Loss: 1.5952, Val Accuracy: 0.3884
Epoch 767/10000, Train Loss: 1.5920, Train Accuracy: 0.3504, Val Loss: 1.5951, Val Accuracy: 0.3884
Epoch 768/10000, Train Loss: 1.5929, Train Accuracy: 0.3449, Val Loss: 1.5951, Val Accuracy: 0.3884
Epoch 769/10000, Train Loss: 1.5929, Train Accuracy: 0.3683, Val Loss: 1.5951, Val Accuracy: 0.3884
Epoch 770/10000, Train Loss: 1.5941, Train Accuracy: 0.3348, Val Loss: 1.5950, Val Accuracy: 0.3884
Epoch 771/10000, Train Loss: 1.5922, Train Accuracy: 0.3627, Val Loss: 1.5950, Val Accuracy: 0.3884
Epoch 772/10000, Train Loss: 1.5918, Train Accuracy: 0.3516, Val Loss: 1.5950, Val Accuracy: 0.3884
Epoch 773/10000, Train Loss: 1.5930, Train Accuracy: 0.3237, Val Loss: 1.5949, Val Accuracy: 0.3884
Epoch 774/10000, Train Loss: 1.5944, Train Accuracy: 0.3125, Val Loss: 1.5949, Val Accuracy: 0.3839
Epoch 775/10000, Train Loss: 1.5932, Train Accuracy: 0.3516, Val Loss: 1.5949, Val Accuracy: 0.3884
Epoch 776/10000, Train Loss: 1.5922, Train Accuracy: 0.3404, Val Loss: 1.5948, Val Accuracy: 0.3884
Epoch 777/10000, Train Loss: 1.5928, Train Accuracy: 0.3348, Val Loss: 1.5948, Val Accuracy: 0.3884
Epoch 778/10000, Train Loss: 1.5935, Train Accuracy: 0.3359, Val Loss: 1.5947, Val Accuracy: 0.3884
Epoch 779/10000, Train Loss: 1.5932, Train Accuracy: 0.3404, Val Loss: 1.5947, Val Accuracy: 0.3884
Epoch 780/10000, Train Loss: 1.5925, Train Accuracy: 0.3583, Val Loss: 1.5947, Val Accuracy: 0.3929
Epoch 781/10000, Train Loss: 1.5931, Train Accuracy: 0.3281, Val Loss: 1.5946, Val Accuracy: 0.3884
Epoch 782/10000, Train Loss: 1.5937, Train Accuracy: 0.3348, Val Loss: 1.5946, Val Accuracy: 0.3884
Epoch 783/10000, Train Loss: 1.5935, Train Accuracy: 0.3382, Val Loss: 1.5946, Val Accuracy: 0.3884
Epoch 784/10000, Train Loss: 1.5918, Train Accuracy: 0.3516, Val Loss: 1.5946, Val Accuracy: 0.3839
Epoch 785/10000, Train Loss: 1.5927, Train Accuracy: 0.3393, Val Loss: 1.5945, Val Accuracy: 0.3839
Epoch 786/10000, Train Loss: 1.5932, Train Accuracy: 0.3192, Val Loss: 1.5945, Val Accuracy: 0.3839
Epoch 787/10000, Train Loss: 1.5918, Train Accuracy: 0.3605, Val Loss: 1.5945, Val Accuracy: 0.3839
Epoch 788/10000, Train Loss: 1.5934, Train Accuracy: 0.3304, Val Loss: 1.5944, Val Accuracy: 0.3884
Epoch 789/10000, Train Loss: 1.5938, Train Accuracy: 0.3315, Val Loss: 1.5944, Val Accuracy: 0.3884
Epoch 790/10000, Train Loss: 1.5917, Train Accuracy: 0.3594, Val Loss: 1.5944, Val Accuracy: 0.3884
Epoch 791/10000, Train Loss: 1.5935, Train Accuracy: 0.3382, Val Loss: 1.5943, Val Accuracy: 0.3884
Epoch 792/10000, Train Loss: 1.5927, Train Accuracy: 0.3348, Val Loss: 1.5943, Val Accuracy: 0.3929
Epoch 793/10000, Train Loss: 1.5924, Train Accuracy: 0.3348, Val Loss: 1.5942, Val Accuracy: 0.3929
Epoch 794/10000, Train Loss: 1.5940, Train Accuracy: 0.3225, Val Loss: 1.5942, Val Accuracy: 0.3929
Epoch 795/10000, Train Loss: 1.5923, Train Accuracy: 0.3192, Val Loss: 1.5941, Val Accuracy: 0.3929
Epoch 796/10000, Train Loss: 1.5916, Train Accuracy: 0.3549, Val Loss: 1.5941, Val Accuracy: 0.3929
Epoch 797/10000, Train Loss: 1.5918, Train Accuracy: 0.3694, Val Loss: 1.5940, Val Accuracy: 0.3973
Epoch 798/10000, Train Loss: 1.5937, Train Accuracy: 0.3315, Val Loss: 1.5940, Val Accuracy: 0.3973
Epoch 799/10000, Train Loss: 1.5934, Train Accuracy: 0.3393, Val Loss: 1.5940, Val Accuracy: 0.3973
Epoch 800/10000, Train Loss: 1.5920, Train Accuracy: 0.3404, Val Loss: 1.5939, Val Accuracy: 0.3973
Epoch 801/10000, Train Loss: 1.5926, Train Accuracy: 0.3438, Val Loss: 1.5939, Val Accuracy: 0.3973
Epoch 802/10000, Train Loss: 1.5929, Train Accuracy: 0.3426, Val Loss: 1.5939, Val Accuracy: 0.3973
Epoch 803/10000, Train Loss: 1.5923, Train Accuracy: 0.3348, Val Loss: 1.5939, Val Accuracy: 0.3973
Epoch 804/10000, Train Loss: 1.5925, Train Accuracy: 0.3449, Val Loss: 1.5938, Val Accuracy: 0.3973
Epoch 805/10000, Train Loss: 1.5929, Train Accuracy: 0.3438, Val Loss: 1.5938, Val Accuracy: 0.3973
Epoch 806/10000, Train Loss: 1.5916, Train Accuracy: 0.3482, Val Loss: 1.5937, Val Accuracy: 0.3929
Epoch 807/10000, Train Loss: 1.5925, Train Accuracy: 0.3426, Val Loss: 1.5937, Val Accuracy: 0.3929
Epoch 808/10000, Train Loss: 1.5915, Train Accuracy: 0.3449, Val Loss: 1.5937, Val Accuracy: 0.3929
Epoch 809/10000, Train Loss: 1.5927, Train Accuracy: 0.3449, Val Loss: 1.5936, Val Accuracy: 0.3929
Epoch 810/10000, Train Loss: 1.5911, Train Accuracy: 0.3482, Val Loss: 1.5936, Val Accuracy: 0.4018
Epoch 811/10000, Train Loss: 1.5917, Train Accuracy: 0.3549, Val Loss: 1.5936, Val Accuracy: 0.3929
Epoch 812/10000, Train Loss: 1.5933, Train Accuracy: 0.3449, Val Loss: 1.5935, Val Accuracy: 0.3973
Epoch 813/10000, Train Loss: 1.5913, Train Accuracy: 0.3650, Val Loss: 1.5935, Val Accuracy: 0.3973
Epoch 814/10000, Train Loss: 1.5913, Train Accuracy: 0.3504, Val Loss: 1.5934, Val Accuracy: 0.3973
Epoch 815/10000, Train Loss: 1.5918, Train Accuracy: 0.3404, Val Loss: 1.5934, Val Accuracy: 0.3973
Epoch 816/10000, Train Loss: 1.5911, Train Accuracy: 0.3393, Val Loss: 1.5934, Val Accuracy: 0.3973
Epoch 817/10000, Train Loss: 1.5928, Train Accuracy: 0.3348, Val Loss: 1.5933, Val Accuracy: 0.3973
Epoch 818/10000, Train Loss: 1.5921, Train Accuracy: 0.3348, Val Loss: 1.5933, Val Accuracy: 0.3973
Epoch 819/10000, Train Loss: 1.5909, Train Accuracy: 0.3571, Val Loss: 1.5933, Val Accuracy: 0.3973
Epoch 820/10000, Train Loss: 1.5915, Train Accuracy: 0.3404, Val Loss: 1.5932, Val Accuracy: 0.3973
Epoch 821/10000, Train Loss: 1.5932, Train Accuracy: 0.3225, Val Loss: 1.5932, Val Accuracy: 0.3973
Epoch 822/10000, Train Loss: 1.5918, Train Accuracy: 0.3348, Val Loss: 1.5931, Val Accuracy: 0.3973
Epoch 823/10000, Train Loss: 1.5912, Train Accuracy: 0.3371, Val Loss: 1.5931, Val Accuracy: 0.4018
Epoch 824/10000, Train Loss: 1.5909, Train Accuracy: 0.3471, Val Loss: 1.5931, Val Accuracy: 0.4018
Epoch 825/10000, Train Loss: 1.5911, Train Accuracy: 0.3438, Val Loss: 1.5930, Val Accuracy: 0.4018
Epoch 826/10000, Train Loss: 1.5927, Train Accuracy: 0.3560, Val Loss: 1.5930, Val Accuracy: 0.4018
Epoch 827/10000, Train Loss: 1.5902, Train Accuracy: 0.3616, Val Loss: 1.5930, Val Accuracy: 0.3973
Epoch 828/10000, Train Loss: 1.5908, Train Accuracy: 0.3571, Val Loss: 1.5929, Val Accuracy: 0.3973
Epoch 829/10000, Train Loss: 1.5917, Train Accuracy: 0.3382, Val Loss: 1.5929, Val Accuracy: 0.3929
Epoch 830/10000, Train Loss: 1.5900, Train Accuracy: 0.3583, Val Loss: 1.5929, Val Accuracy: 0.3973
Epoch 831/10000, Train Loss: 1.5909, Train Accuracy: 0.3504, Val Loss: 1.5928, Val Accuracy: 0.3929
Epoch 832/10000, Train Loss: 1.5900, Train Accuracy: 0.3683, Val Loss: 1.5928, Val Accuracy: 0.3929
Epoch 833/10000, Train Loss: 1.5908, Train Accuracy: 0.3493, Val Loss: 1.5928, Val Accuracy: 0.3929
Epoch 834/10000, Train Loss: 1.5911, Train Accuracy: 0.3527, Val Loss: 1.5927, Val Accuracy: 0.3929
Epoch 835/10000, Train Loss: 1.5908, Train Accuracy: 0.3304, Val Loss: 1.5927, Val Accuracy: 0.3929
Epoch 836/10000, Train Loss: 1.5897, Train Accuracy: 0.3493, Val Loss: 1.5926, Val Accuracy: 0.3929
Epoch 837/10000, Train Loss: 1.5901, Train Accuracy: 0.3493, Val Loss: 1.5926, Val Accuracy: 0.3929
Epoch 838/10000, Train Loss: 1.5892, Train Accuracy: 0.3638, Val Loss: 1.5926, Val Accuracy: 0.3929
Epoch 839/10000, Train Loss: 1.5908, Train Accuracy: 0.3504, Val Loss: 1.5925, Val Accuracy: 0.3929
Epoch 840/10000, Train Loss: 1.5912, Train Accuracy: 0.3650, Val Loss: 1.5925, Val Accuracy: 0.3929
Epoch 841/10000, Train Loss: 1.5905, Train Accuracy: 0.3471, Val Loss: 1.5924, Val Accuracy: 0.3929
Epoch 842/10000, Train Loss: 1.5906, Train Accuracy: 0.3460, Val Loss: 1.5924, Val Accuracy: 0.3929
Epoch 843/10000, Train Loss: 1.5899, Train Accuracy: 0.3571, Val Loss: 1.5923, Val Accuracy: 0.3929
Epoch 844/10000, Train Loss: 1.5910, Train Accuracy: 0.3438, Val Loss: 1.5923, Val Accuracy: 0.3929
Epoch 845/10000, Train Loss: 1.5918, Train Accuracy: 0.3292, Val Loss: 1.5922, Val Accuracy: 0.3929
Epoch 846/10000, Train Loss: 1.5920, Train Accuracy: 0.3382, Val Loss: 1.5922, Val Accuracy: 0.3929
Epoch 847/10000, Train Loss: 1.5907, Train Accuracy: 0.3415, Val Loss: 1.5922, Val Accuracy: 0.3929
Epoch 848/10000, Train Loss: 1.5909, Train Accuracy: 0.3404, Val Loss: 1.5921, Val Accuracy: 0.3929
Epoch 849/10000, Train Loss: 1.5897, Train Accuracy: 0.3650, Val Loss: 1.5921, Val Accuracy: 0.3929
Epoch 850/10000, Train Loss: 1.5904, Train Accuracy: 0.3348, Val Loss: 1.5920, Val Accuracy: 0.3929
Epoch 851/10000, Train Loss: 1.5899, Train Accuracy: 0.3516, Val Loss: 1.5920, Val Accuracy: 0.3929
Epoch 852/10000, Train Loss: 1.5899, Train Accuracy: 0.3527, Val Loss: 1.5920, Val Accuracy: 0.3929
Epoch 853/10000, Train Loss: 1.5906, Train Accuracy: 0.3549, Val Loss: 1.5919, Val Accuracy: 0.3884
Epoch 854/10000, Train Loss: 1.5894, Train Accuracy: 0.3560, Val Loss: 1.5919, Val Accuracy: 0.3929
Epoch 855/10000, Train Loss: 1.5893, Train Accuracy: 0.3538, Val Loss: 1.5918, Val Accuracy: 0.3929
Epoch 856/10000, Train Loss: 1.5908, Train Accuracy: 0.3627, Val Loss: 1.5918, Val Accuracy: 0.3973
Epoch 857/10000, Train Loss: 1.5898, Train Accuracy: 0.3683, Val Loss: 1.5918, Val Accuracy: 0.3973
Epoch 858/10000, Train Loss: 1.5896, Train Accuracy: 0.3772, Val Loss: 1.5917, Val Accuracy: 0.3973
Epoch 859/10000, Train Loss: 1.5911, Train Accuracy: 0.3404, Val Loss: 1.5917, Val Accuracy: 0.3973
Epoch 860/10000, Train Loss: 1.5906, Train Accuracy: 0.3415, Val Loss: 1.5916, Val Accuracy: 0.3973
Epoch 861/10000, Train Loss: 1.5908, Train Accuracy: 0.3371, Val Loss: 1.5916, Val Accuracy: 0.3973
Epoch 862/10000, Train Loss: 1.5912, Train Accuracy: 0.3404, Val Loss: 1.5916, Val Accuracy: 0.3973
Epoch 863/10000, Train Loss: 1.5898, Train Accuracy: 0.3482, Val Loss: 1.5915, Val Accuracy: 0.3973
Epoch 864/10000, Train Loss: 1.5888, Train Accuracy: 0.3538, Val Loss: 1.5915, Val Accuracy: 0.3973
Epoch 865/10000, Train Loss: 1.5898, Train Accuracy: 0.3605, Val Loss: 1.5915, Val Accuracy: 0.3973
Epoch 866/10000, Train Loss: 1.5905, Train Accuracy: 0.3315, Val Loss: 1.5914, Val Accuracy: 0.3973
Epoch 867/10000, Train Loss: 1.5904, Train Accuracy: 0.3449, Val Loss: 1.5914, Val Accuracy: 0.3973
Epoch 868/10000, Train Loss: 1.5901, Train Accuracy: 0.3449, Val Loss: 1.5913, Val Accuracy: 0.3973
Epoch 869/10000, Train Loss: 1.5887, Train Accuracy: 0.3471, Val Loss: 1.5913, Val Accuracy: 0.3973
Epoch 870/10000, Train Loss: 1.5876, Train Accuracy: 0.3705, Val Loss: 1.5912, Val Accuracy: 0.3973
Epoch 871/10000, Train Loss: 1.5896, Train Accuracy: 0.3404, Val Loss: 1.5912, Val Accuracy: 0.3973
Epoch 872/10000, Train Loss: 1.5901, Train Accuracy: 0.3382, Val Loss: 1.5911, Val Accuracy: 0.4018
Epoch 873/10000, Train Loss: 1.5907, Train Accuracy: 0.3237, Val Loss: 1.5911, Val Accuracy: 0.4018
Epoch 874/10000, Train Loss: 1.5876, Train Accuracy: 0.3594, Val Loss: 1.5911, Val Accuracy: 0.4018
Epoch 875/10000, Train Loss: 1.5890, Train Accuracy: 0.3359, Val Loss: 1.5910, Val Accuracy: 0.4018
Epoch 876/10000, Train Loss: 1.5905, Train Accuracy: 0.3516, Val Loss: 1.5910, Val Accuracy: 0.4018
Epoch 877/10000, Train Loss: 1.5879, Train Accuracy: 0.3661, Val Loss: 1.5909, Val Accuracy: 0.4018
Epoch 878/10000, Train Loss: 1.5898, Train Accuracy: 0.3504, Val Loss: 1.5909, Val Accuracy: 0.4018
Epoch 879/10000, Train Loss: 1.5886, Train Accuracy: 0.3583, Val Loss: 1.5908, Val Accuracy: 0.4018
Epoch 880/10000, Train Loss: 1.5898, Train Accuracy: 0.3482, Val Loss: 1.5908, Val Accuracy: 0.4018
Epoch 881/10000, Train Loss: 1.5894, Train Accuracy: 0.3560, Val Loss: 1.5907, Val Accuracy: 0.4062
Epoch 882/10000, Train Loss: 1.5900, Train Accuracy: 0.3449, Val Loss: 1.5906, Val Accuracy: 0.4062
Epoch 883/10000, Train Loss: 1.5876, Train Accuracy: 0.3761, Val Loss: 1.5906, Val Accuracy: 0.4062
Epoch 884/10000, Train Loss: 1.5894, Train Accuracy: 0.3538, Val Loss: 1.5906, Val Accuracy: 0.4062
Epoch 885/10000, Train Loss: 1.5894, Train Accuracy: 0.3315, Val Loss: 1.5906, Val Accuracy: 0.4062
Epoch 886/10000, Train Loss: 1.5899, Train Accuracy: 0.3638, Val Loss: 1.5905, Val Accuracy: 0.4062
Epoch 887/10000, Train Loss: 1.5878, Train Accuracy: 0.3583, Val Loss: 1.5905, Val Accuracy: 0.4062
Epoch 888/10000, Train Loss: 1.5871, Train Accuracy: 0.3705, Val Loss: 1.5904, Val Accuracy: 0.4062
Epoch 889/10000, Train Loss: 1.5879, Train Accuracy: 0.3739, Val Loss: 1.5904, Val Accuracy: 0.4062
Epoch 890/10000, Train Loss: 1.5879, Train Accuracy: 0.3627, Val Loss: 1.5903, Val Accuracy: 0.4062
Epoch 891/10000, Train Loss: 1.5877, Train Accuracy: 0.3538, Val Loss: 1.5903, Val Accuracy: 0.4062
Epoch 892/10000, Train Loss: 1.5883, Train Accuracy: 0.3571, Val Loss: 1.5902, Val Accuracy: 0.4062
Epoch 893/10000, Train Loss: 1.5874, Train Accuracy: 0.3549, Val Loss: 1.5902, Val Accuracy: 0.4062
Epoch 894/10000, Train Loss: 1.5895, Train Accuracy: 0.3371, Val Loss: 1.5901, Val Accuracy: 0.4107
Epoch 895/10000, Train Loss: 1.5877, Train Accuracy: 0.3594, Val Loss: 1.5901, Val Accuracy: 0.4107
Epoch 896/10000, Train Loss: 1.5883, Train Accuracy: 0.3426, Val Loss: 1.5900, Val Accuracy: 0.4107
Epoch 897/10000, Train Loss: 1.5892, Train Accuracy: 0.3493, Val Loss: 1.5900, Val Accuracy: 0.4107
Epoch 898/10000, Train Loss: 1.5887, Train Accuracy: 0.3549, Val Loss: 1.5899, Val Accuracy: 0.4107
Epoch 899/10000, Train Loss: 1.5868, Train Accuracy: 0.3650, Val Loss: 1.5899, Val Accuracy: 0.4107
Epoch 900/10000, Train Loss: 1.5875, Train Accuracy: 0.3504, Val Loss: 1.5898, Val Accuracy: 0.4107
Epoch 901/10000, Train Loss: 1.5877, Train Accuracy: 0.3460, Val Loss: 1.5898, Val Accuracy: 0.4107
Epoch 902/10000, Train Loss: 1.5884, Train Accuracy: 0.3605, Val Loss: 1.5898, Val Accuracy: 0.4107
Epoch 903/10000, Train Loss: 1.5875, Train Accuracy: 0.3594, Val Loss: 1.5897, Val Accuracy: 0.4107
Epoch 904/10000, Train Loss: 1.5893, Train Accuracy: 0.3650, Val Loss: 1.5897, Val Accuracy: 0.4107
Epoch 905/10000, Train Loss: 1.5865, Train Accuracy: 0.3616, Val Loss: 1.5896, Val Accuracy: 0.4062
Epoch 906/10000, Train Loss: 1.5876, Train Accuracy: 0.3806, Val Loss: 1.5896, Val Accuracy: 0.4062
Epoch 907/10000, Train Loss: 1.5859, Train Accuracy: 0.3772, Val Loss: 1.5895, Val Accuracy: 0.4062
Epoch 908/10000, Train Loss: 1.5879, Train Accuracy: 0.3672, Val Loss: 1.5895, Val Accuracy: 0.4062
Epoch 909/10000, Train Loss: 1.5865, Train Accuracy: 0.3694, Val Loss: 1.5894, Val Accuracy: 0.4062
Epoch 910/10000, Train Loss: 1.5884, Train Accuracy: 0.3538, Val Loss: 1.5894, Val Accuracy: 0.4062
Epoch 911/10000, Train Loss: 1.5890, Train Accuracy: 0.3404, Val Loss: 1.5893, Val Accuracy: 0.4062
Epoch 912/10000, Train Loss: 1.5875, Train Accuracy: 0.3661, Val Loss: 1.5893, Val Accuracy: 0.4062
Epoch 913/10000, Train Loss: 1.5895, Train Accuracy: 0.3315, Val Loss: 1.5892, Val Accuracy: 0.4062
Epoch 914/10000, Train Loss: 1.5872, Train Accuracy: 0.3638, Val Loss: 1.5892, Val Accuracy: 0.4062
Epoch 915/10000, Train Loss: 1.5872, Train Accuracy: 0.3460, Val Loss: 1.5892, Val Accuracy: 0.4062
Epoch 916/10000, Train Loss: 1.5877, Train Accuracy: 0.3460, Val Loss: 1.5891, Val Accuracy: 0.4062
Epoch 917/10000, Train Loss: 1.5875, Train Accuracy: 0.3516, Val Loss: 1.5891, Val Accuracy: 0.4062
Epoch 918/10000, Train Loss: 1.5870, Train Accuracy: 0.3560, Val Loss: 1.5890, Val Accuracy: 0.4062
Epoch 919/10000, Train Loss: 1.5867, Train Accuracy: 0.3460, Val Loss: 1.5890, Val Accuracy: 0.4062
Epoch 920/10000, Train Loss: 1.5870, Train Accuracy: 0.3527, Val Loss: 1.5889, Val Accuracy: 0.4107
Epoch 921/10000, Train Loss: 1.5870, Train Accuracy: 0.3605, Val Loss: 1.5889, Val Accuracy: 0.4062
Epoch 922/10000, Train Loss: 1.5873, Train Accuracy: 0.3571, Val Loss: 1.5888, Val Accuracy: 0.4062
Epoch 923/10000, Train Loss: 1.5875, Train Accuracy: 0.3594, Val Loss: 1.5887, Val Accuracy: 0.4062
Epoch 924/10000, Train Loss: 1.5878, Train Accuracy: 0.3460, Val Loss: 1.5887, Val Accuracy: 0.4062
Epoch 925/10000, Train Loss: 1.5870, Train Accuracy: 0.3438, Val Loss: 1.5886, Val Accuracy: 0.4062
Epoch 926/10000, Train Loss: 1.5858, Train Accuracy: 0.3538, Val Loss: 1.5886, Val Accuracy: 0.4062
Epoch 927/10000, Train Loss: 1.5875, Train Accuracy: 0.3560, Val Loss: 1.5886, Val Accuracy: 0.4062
Epoch 928/10000, Train Loss: 1.5862, Train Accuracy: 0.3449, Val Loss: 1.5885, Val Accuracy: 0.4062
Epoch 929/10000, Train Loss: 1.5861, Train Accuracy: 0.3661, Val Loss: 1.5885, Val Accuracy: 0.4062
Epoch 930/10000, Train Loss: 1.5863, Train Accuracy: 0.3571, Val Loss: 1.5884, Val Accuracy: 0.4062
Epoch 931/10000, Train Loss: 1.5873, Train Accuracy: 0.3650, Val Loss: 1.5884, Val Accuracy: 0.4062
Epoch 932/10000, Train Loss: 1.5872, Train Accuracy: 0.3371, Val Loss: 1.5883, Val Accuracy: 0.4062
Epoch 933/10000, Train Loss: 1.5867, Train Accuracy: 0.3504, Val Loss: 1.5882, Val Accuracy: 0.4062
Epoch 934/10000, Train Loss: 1.5865, Train Accuracy: 0.3571, Val Loss: 1.5882, Val Accuracy: 0.4062
Epoch 935/10000, Train Loss: 1.5854, Train Accuracy: 0.3683, Val Loss: 1.5881, Val Accuracy: 0.4062
Epoch 936/10000, Train Loss: 1.5860, Train Accuracy: 0.3627, Val Loss: 1.5881, Val Accuracy: 0.4062
Epoch 937/10000, Train Loss: 1.5852, Train Accuracy: 0.3605, Val Loss: 1.5880, Val Accuracy: 0.4062
Epoch 938/10000, Train Loss: 1.5853, Train Accuracy: 0.3694, Val Loss: 1.5880, Val Accuracy: 0.4062
Epoch 939/10000, Train Loss: 1.5871, Train Accuracy: 0.3694, Val Loss: 1.5879, Val Accuracy: 0.4018
Epoch 940/10000, Train Loss: 1.5854, Train Accuracy: 0.3616, Val Loss: 1.5879, Val Accuracy: 0.4018
Epoch 941/10000, Train Loss: 1.5864, Train Accuracy: 0.3538, Val Loss: 1.5878, Val Accuracy: 0.4062
Epoch 942/10000, Train Loss: 1.5872, Train Accuracy: 0.3739, Val Loss: 1.5878, Val Accuracy: 0.4062
Epoch 943/10000, Train Loss: 1.5855, Train Accuracy: 0.3538, Val Loss: 1.5877, Val Accuracy: 0.4062
Epoch 944/10000, Train Loss: 1.5848, Train Accuracy: 0.3906, Val Loss: 1.5877, Val Accuracy: 0.4062
Epoch 945/10000, Train Loss: 1.5854, Train Accuracy: 0.3761, Val Loss: 1.5876, Val Accuracy: 0.4062
Epoch 946/10000, Train Loss: 1.5854, Train Accuracy: 0.3571, Val Loss: 1.5876, Val Accuracy: 0.4062
Epoch 947/10000, Train Loss: 1.5858, Train Accuracy: 0.3594, Val Loss: 1.5875, Val Accuracy: 0.4062
Epoch 948/10000, Train Loss: 1.5847, Train Accuracy: 0.3482, Val Loss: 1.5875, Val Accuracy: 0.4018
Epoch 949/10000, Train Loss: 1.5855, Train Accuracy: 0.3348, Val Loss: 1.5874, Val Accuracy: 0.4018
Epoch 950/10000, Train Loss: 1.5856, Train Accuracy: 0.3739, Val Loss: 1.5874, Val Accuracy: 0.3973
Epoch 951/10000, Train Loss: 1.5864, Train Accuracy: 0.3705, Val Loss: 1.5873, Val Accuracy: 0.3973
Epoch 952/10000, Train Loss: 1.5859, Train Accuracy: 0.3549, Val Loss: 1.5872, Val Accuracy: 0.3973
Epoch 953/10000, Train Loss: 1.5847, Train Accuracy: 0.3694, Val Loss: 1.5872, Val Accuracy: 0.3973
Epoch 954/10000, Train Loss: 1.5843, Train Accuracy: 0.3828, Val Loss: 1.5871, Val Accuracy: 0.3973
Epoch 955/10000, Train Loss: 1.5849, Train Accuracy: 0.3627, Val Loss: 1.5871, Val Accuracy: 0.3973
Epoch 956/10000, Train Loss: 1.5848, Train Accuracy: 0.3594, Val Loss: 1.5870, Val Accuracy: 0.3973
Epoch 957/10000, Train Loss: 1.5848, Train Accuracy: 0.3638, Val Loss: 1.5870, Val Accuracy: 0.3973
Epoch 958/10000, Train Loss: 1.5869, Train Accuracy: 0.3471, Val Loss: 1.5869, Val Accuracy: 0.3973
Epoch 959/10000, Train Loss: 1.5857, Train Accuracy: 0.3393, Val Loss: 1.5869, Val Accuracy: 0.3973
Epoch 960/10000, Train Loss: 1.5829, Train Accuracy: 0.3750, Val Loss: 1.5868, Val Accuracy: 0.3973
Epoch 961/10000, Train Loss: 1.5849, Train Accuracy: 0.3627, Val Loss: 1.5868, Val Accuracy: 0.3973
Epoch 962/10000, Train Loss: 1.5854, Train Accuracy: 0.3382, Val Loss: 1.5867, Val Accuracy: 0.3973
Epoch 963/10000, Train Loss: 1.5846, Train Accuracy: 0.3538, Val Loss: 1.5867, Val Accuracy: 0.3973
Epoch 964/10000, Train Loss: 1.5839, Train Accuracy: 0.3583, Val Loss: 1.5866, Val Accuracy: 0.3973
Epoch 965/10000, Train Loss: 1.5843, Train Accuracy: 0.3638, Val Loss: 1.5865, Val Accuracy: 0.3973
Epoch 966/10000, Train Loss: 1.5865, Train Accuracy: 0.3337, Val Loss: 1.5865, Val Accuracy: 0.3973
Epoch 967/10000, Train Loss: 1.5860, Train Accuracy: 0.3549, Val Loss: 1.5864, Val Accuracy: 0.3973
Epoch 968/10000, Train Loss: 1.5852, Train Accuracy: 0.3594, Val Loss: 1.5864, Val Accuracy: 0.3973
Epoch 969/10000, Train Loss: 1.5855, Train Accuracy: 0.3549, Val Loss: 1.5863, Val Accuracy: 0.3973
Epoch 970/10000, Train Loss: 1.5854, Train Accuracy: 0.3638, Val Loss: 1.5862, Val Accuracy: 0.3973
Epoch 971/10000, Train Loss: 1.5847, Train Accuracy: 0.3426, Val Loss: 1.5862, Val Accuracy: 0.3973
Epoch 972/10000, Train Loss: 1.5834, Train Accuracy: 0.3627, Val Loss: 1.5862, Val Accuracy: 0.3973
Epoch 973/10000, Train Loss: 1.5847, Train Accuracy: 0.3571, Val Loss: 1.5861, Val Accuracy: 0.3973
Epoch 974/10000, Train Loss: 1.5840, Train Accuracy: 0.3571, Val Loss: 1.5861, Val Accuracy: 0.3973
Epoch 975/10000, Train Loss: 1.5845, Train Accuracy: 0.3594, Val Loss: 1.5860, Val Accuracy: 0.3973
Epoch 976/10000, Train Loss: 1.5834, Train Accuracy: 0.3560, Val Loss: 1.5859, Val Accuracy: 0.3973
Epoch 977/10000, Train Loss: 1.5834, Train Accuracy: 0.3605, Val Loss: 1.5859, Val Accuracy: 0.3973
Epoch 978/10000, Train Loss: 1.5825, Train Accuracy: 0.3850, Val Loss: 1.5858, Val Accuracy: 0.3973
Epoch 979/10000, Train Loss: 1.5836, Train Accuracy: 0.3661, Val Loss: 1.5858, Val Accuracy: 0.3973
Epoch 980/10000, Train Loss: 1.5829, Train Accuracy: 0.3750, Val Loss: 1.5857, Val Accuracy: 0.3973
Epoch 981/10000, Train Loss: 1.5827, Train Accuracy: 0.3694, Val Loss: 1.5857, Val Accuracy: 0.3973
Epoch 982/10000, Train Loss: 1.5847, Train Accuracy: 0.3527, Val Loss: 1.5856, Val Accuracy: 0.3973
Epoch 983/10000, Train Loss: 1.5850, Train Accuracy: 0.3650, Val Loss: 1.5856, Val Accuracy: 0.3973
Epoch 984/10000, Train Loss: 1.5836, Train Accuracy: 0.3728, Val Loss: 1.5855, Val Accuracy: 0.3973
Epoch 985/10000, Train Loss: 1.5839, Train Accuracy: 0.3616, Val Loss: 1.5854, Val Accuracy: 0.3973
Epoch 986/10000, Train Loss: 1.5816, Train Accuracy: 0.3750, Val Loss: 1.5854, Val Accuracy: 0.3973
Epoch 987/10000, Train Loss: 1.5820, Train Accuracy: 0.3493, Val Loss: 1.5853, Val Accuracy: 0.3973
Epoch 988/10000, Train Loss: 1.5832, Train Accuracy: 0.3683, Val Loss: 1.5853, Val Accuracy: 0.3973
Epoch 989/10000, Train Loss: 1.5814, Train Accuracy: 0.3717, Val Loss: 1.5852, Val Accuracy: 0.3929
Epoch 990/10000, Train Loss: 1.5847, Train Accuracy: 0.3605, Val Loss: 1.5851, Val Accuracy: 0.3929
Epoch 991/10000, Train Loss: 1.5820, Train Accuracy: 0.3616, Val Loss: 1.5850, Val Accuracy: 0.3929
Epoch 992/10000, Train Loss: 1.5831, Train Accuracy: 0.3661, Val Loss: 1.5850, Val Accuracy: 0.3929
Epoch 993/10000, Train Loss: 1.5837, Train Accuracy: 0.3616, Val Loss: 1.5849, Val Accuracy: 0.3929
Epoch 994/10000, Train Loss: 1.5836, Train Accuracy: 0.3638, Val Loss: 1.5848, Val Accuracy: 0.3884
Epoch 995/10000, Train Loss: 1.5831, Train Accuracy: 0.3638, Val Loss: 1.5848, Val Accuracy: 0.3884
Epoch 996/10000, Train Loss: 1.5836, Train Accuracy: 0.3549, Val Loss: 1.5847, Val Accuracy: 0.3884
Epoch 997/10000, Train Loss: 1.5831, Train Accuracy: 0.3348, Val Loss: 1.5847, Val Accuracy: 0.3884
Epoch 998/10000, Train Loss: 1.5827, Train Accuracy: 0.3717, Val Loss: 1.5846, Val Accuracy: 0.3884
Epoch 999/10000, Train Loss: 1.5839, Train Accuracy: 0.3705, Val Loss: 1.5846, Val Accuracy: 0.3884
Epoch 1000/10000, Train Loss: 1.5850, Train Accuracy: 0.3527, Val Loss: 1.5845, Val Accuracy: 0.3884
Epoch 1001/10000, Train Loss: 1.5826, Train Accuracy: 0.3672, Val Loss: 1.5844, Val Accuracy: 0.3884
Epoch 1002/10000, Train Loss: 1.5813, Train Accuracy: 0.3694, Val Loss: 1.5844, Val Accuracy: 0.3884
Epoch 1003/10000, Train Loss: 1.5820, Train Accuracy: 0.3728, Val Loss: 1.5843, Val Accuracy: 0.3884
Epoch 1004/10000, Train Loss: 1.5827, Train Accuracy: 0.3795, Val Loss: 1.5842, Val Accuracy: 0.3884
Epoch 1005/10000, Train Loss: 1.5789, Train Accuracy: 0.3862, Val Loss: 1.5842, Val Accuracy: 0.3884
Epoch 1006/10000, Train Loss: 1.5812, Train Accuracy: 0.3873, Val Loss: 1.5841, Val Accuracy: 0.3884
Epoch 1007/10000, Train Loss: 1.5819, Train Accuracy: 0.3728, Val Loss: 1.5840, Val Accuracy: 0.3884
Epoch 1008/10000, Train Loss: 1.5821, Train Accuracy: 0.3527, Val Loss: 1.5840, Val Accuracy: 0.3884
Epoch 1009/10000, Train Loss: 1.5835, Train Accuracy: 0.3616, Val Loss: 1.5839, Val Accuracy: 0.3884
Epoch 1010/10000, Train Loss: 1.5802, Train Accuracy: 0.3616, Val Loss: 1.5839, Val Accuracy: 0.3884
Epoch 1011/10000, Train Loss: 1.5829, Train Accuracy: 0.3739, Val Loss: 1.5838, Val Accuracy: 0.3884
Epoch 1012/10000, Train Loss: 1.5811, Train Accuracy: 0.3638, Val Loss: 1.5837, Val Accuracy: 0.3884
Epoch 1013/10000, Train Loss: 1.5822, Train Accuracy: 0.3650, Val Loss: 1.5837, Val Accuracy: 0.3884
Epoch 1014/10000, Train Loss: 1.5800, Train Accuracy: 0.3873, Val Loss: 1.5836, Val Accuracy: 0.3884
Epoch 1015/10000, Train Loss: 1.5816, Train Accuracy: 0.3996, Val Loss: 1.5836, Val Accuracy: 0.3884
Epoch 1016/10000, Train Loss: 1.5846, Train Accuracy: 0.3571, Val Loss: 1.5835, Val Accuracy: 0.3884
Epoch 1017/10000, Train Loss: 1.5822, Train Accuracy: 0.3650, Val Loss: 1.5834, Val Accuracy: 0.3884
Epoch 1018/10000, Train Loss: 1.5782, Train Accuracy: 0.3940, Val Loss: 1.5833, Val Accuracy: 0.3884
Epoch 1019/10000, Train Loss: 1.5820, Train Accuracy: 0.3493, Val Loss: 1.5832, Val Accuracy: 0.3884
Epoch 1020/10000, Train Loss: 1.5811, Train Accuracy: 0.3850, Val Loss: 1.5832, Val Accuracy: 0.3884
Epoch 1021/10000, Train Loss: 1.5828, Train Accuracy: 0.3583, Val Loss: 1.5831, Val Accuracy: 0.3884
Epoch 1022/10000, Train Loss: 1.5792, Train Accuracy: 0.3873, Val Loss: 1.5831, Val Accuracy: 0.3884
Epoch 1023/10000, Train Loss: 1.5823, Train Accuracy: 0.3571, Val Loss: 1.5830, Val Accuracy: 0.3884
Epoch 1024/10000, Train Loss: 1.5815, Train Accuracy: 0.3739, Val Loss: 1.5829, Val Accuracy: 0.3884
Epoch 1025/10000, Train Loss: 1.5809, Train Accuracy: 0.3761, Val Loss: 1.5829, Val Accuracy: 0.3884
Epoch 1026/10000, Train Loss: 1.5818, Train Accuracy: 0.3672, Val Loss: 1.5828, Val Accuracy: 0.3884
Epoch 1027/10000, Train Loss: 1.5802, Train Accuracy: 0.3627, Val Loss: 1.5828, Val Accuracy: 0.3884
Epoch 1028/10000, Train Loss: 1.5808, Train Accuracy: 0.3683, Val Loss: 1.5827, Val Accuracy: 0.3884
Epoch 1029/10000, Train Loss: 1.5795, Train Accuracy: 0.3940, Val Loss: 1.5826, Val Accuracy: 0.3884
Epoch 1030/10000, Train Loss: 1.5804, Train Accuracy: 0.3527, Val Loss: 1.5826, Val Accuracy: 0.3884
Epoch 1031/10000, Train Loss: 1.5803, Train Accuracy: 0.3817, Val Loss: 1.5825, Val Accuracy: 0.3884
Epoch 1032/10000, Train Loss: 1.5782, Train Accuracy: 0.3828, Val Loss: 1.5825, Val Accuracy: 0.3884
Epoch 1033/10000, Train Loss: 1.5789, Train Accuracy: 0.3661, Val Loss: 1.5824, Val Accuracy: 0.3884
Epoch 1034/10000, Train Loss: 1.5792, Train Accuracy: 0.3750, Val Loss: 1.5823, Val Accuracy: 0.3884
Epoch 1035/10000, Train Loss: 1.5813, Train Accuracy: 0.3516, Val Loss: 1.5822, Val Accuracy: 0.3884
Epoch 1036/10000, Train Loss: 1.5797, Train Accuracy: 0.3705, Val Loss: 1.5822, Val Accuracy: 0.3884
Epoch 1037/10000, Train Loss: 1.5813, Train Accuracy: 0.3683, Val Loss: 1.5821, Val Accuracy: 0.3884
Epoch 1038/10000, Train Loss: 1.5789, Train Accuracy: 0.3705, Val Loss: 1.5820, Val Accuracy: 0.3884
Epoch 1039/10000, Train Loss: 1.5807, Train Accuracy: 0.3638, Val Loss: 1.5820, Val Accuracy: 0.3884
Epoch 1040/10000, Train Loss: 1.5801, Train Accuracy: 0.3627, Val Loss: 1.5819, Val Accuracy: 0.3884
Epoch 1041/10000, Train Loss: 1.5813, Train Accuracy: 0.3661, Val Loss: 1.5818, Val Accuracy: 0.3929
Epoch 1042/10000, Train Loss: 1.5798, Train Accuracy: 0.3571, Val Loss: 1.5817, Val Accuracy: 0.3929
Epoch 1043/10000, Train Loss: 1.5806, Train Accuracy: 0.3605, Val Loss: 1.5817, Val Accuracy: 0.3929
Epoch 1044/10000, Train Loss: 1.5746, Train Accuracy: 0.4085, Val Loss: 1.5816, Val Accuracy: 0.3929
Epoch 1045/10000, Train Loss: 1.5795, Train Accuracy: 0.3828, Val Loss: 1.5815, Val Accuracy: 0.3973
Epoch 1046/10000, Train Loss: 1.5770, Train Accuracy: 0.3917, Val Loss: 1.5815, Val Accuracy: 0.3973
Epoch 1047/10000, Train Loss: 1.5790, Train Accuracy: 0.3795, Val Loss: 1.5814, Val Accuracy: 0.3973
Epoch 1048/10000, Train Loss: 1.5787, Train Accuracy: 0.3739, Val Loss: 1.5813, Val Accuracy: 0.3973
Epoch 1049/10000, Train Loss: 1.5799, Train Accuracy: 0.3650, Val Loss: 1.5813, Val Accuracy: 0.3973
Epoch 1050/10000, Train Loss: 1.5775, Train Accuracy: 0.3828, Val Loss: 1.5812, Val Accuracy: 0.3973
Epoch 1051/10000, Train Loss: 1.5787, Train Accuracy: 0.3761, Val Loss: 1.5811, Val Accuracy: 0.3973
Epoch 1052/10000, Train Loss: 1.5782, Train Accuracy: 0.3650, Val Loss: 1.5810, Val Accuracy: 0.3973
Epoch 1053/10000, Train Loss: 1.5773, Train Accuracy: 0.3783, Val Loss: 1.5810, Val Accuracy: 0.3973
Epoch 1054/10000, Train Loss: 1.5826, Train Accuracy: 0.3393, Val Loss: 1.5808, Val Accuracy: 0.3973
Epoch 1055/10000, Train Loss: 1.5783, Train Accuracy: 0.3538, Val Loss: 1.5808, Val Accuracy: 0.3973
Epoch 1056/10000, Train Loss: 1.5791, Train Accuracy: 0.3717, Val Loss: 1.5807, Val Accuracy: 0.3973
Epoch 1057/10000, Train Loss: 1.5767, Train Accuracy: 0.3783, Val Loss: 1.5806, Val Accuracy: 0.3973
Epoch 1058/10000, Train Loss: 1.5778, Train Accuracy: 0.3895, Val Loss: 1.5806, Val Accuracy: 0.3973
Epoch 1059/10000, Train Loss: 1.5788, Train Accuracy: 0.3795, Val Loss: 1.5805, Val Accuracy: 0.3973
Epoch 1060/10000, Train Loss: 1.5792, Train Accuracy: 0.3438, Val Loss: 1.5805, Val Accuracy: 0.3973
Epoch 1061/10000, Train Loss: 1.5778, Train Accuracy: 0.3616, Val Loss: 1.5804, Val Accuracy: 0.3973
Epoch 1062/10000, Train Loss: 1.5792, Train Accuracy: 0.3627, Val Loss: 1.5803, Val Accuracy: 0.3973
Epoch 1063/10000, Train Loss: 1.5805, Train Accuracy: 0.3493, Val Loss: 1.5802, Val Accuracy: 0.3973
Epoch 1064/10000, Train Loss: 1.5787, Train Accuracy: 0.3415, Val Loss: 1.5801, Val Accuracy: 0.3973
Epoch 1065/10000, Train Loss: 1.5773, Train Accuracy: 0.3772, Val Loss: 1.5801, Val Accuracy: 0.3973
Epoch 1066/10000, Train Loss: 1.5781, Train Accuracy: 0.3783, Val Loss: 1.5800, Val Accuracy: 0.3973
Epoch 1067/10000, Train Loss: 1.5783, Train Accuracy: 0.3560, Val Loss: 1.5799, Val Accuracy: 0.3973
Epoch 1068/10000, Train Loss: 1.5773, Train Accuracy: 0.3750, Val Loss: 1.5798, Val Accuracy: 0.3973
Epoch 1069/10000, Train Loss: 1.5788, Train Accuracy: 0.3705, Val Loss: 1.5798, Val Accuracy: 0.3973
Epoch 1070/10000, Train Loss: 1.5776, Train Accuracy: 0.3627, Val Loss: 1.5797, Val Accuracy: 0.3973
Epoch 1071/10000, Train Loss: 1.5786, Train Accuracy: 0.3828, Val Loss: 1.5796, Val Accuracy: 0.4018
Epoch 1072/10000, Train Loss: 1.5782, Train Accuracy: 0.3616, Val Loss: 1.5795, Val Accuracy: 0.4018
Epoch 1073/10000, Train Loss: 1.5771, Train Accuracy: 0.3884, Val Loss: 1.5795, Val Accuracy: 0.4018
Epoch 1074/10000, Train Loss: 1.5766, Train Accuracy: 0.3884, Val Loss: 1.5794, Val Accuracy: 0.4018
Epoch 1075/10000, Train Loss: 1.5773, Train Accuracy: 0.3661, Val Loss: 1.5793, Val Accuracy: 0.4018
Epoch 1076/10000, Train Loss: 1.5771, Train Accuracy: 0.3929, Val Loss: 1.5793, Val Accuracy: 0.4018
Epoch 1077/10000, Train Loss: 1.5776, Train Accuracy: 0.3739, Val Loss: 1.5792, Val Accuracy: 0.4018
Epoch 1078/10000, Train Loss: 1.5752, Train Accuracy: 0.3761, Val Loss: 1.5791, Val Accuracy: 0.4018
Epoch 1079/10000, Train Loss: 1.5781, Train Accuracy: 0.3705, Val Loss: 1.5790, Val Accuracy: 0.4018
Epoch 1080/10000, Train Loss: 1.5773, Train Accuracy: 0.3705, Val Loss: 1.5789, Val Accuracy: 0.4018
Epoch 1081/10000, Train Loss: 1.5770, Train Accuracy: 0.3672, Val Loss: 1.5789, Val Accuracy: 0.4018
Epoch 1082/10000, Train Loss: 1.5770, Train Accuracy: 0.3839, Val Loss: 1.5788, Val Accuracy: 0.4018
Epoch 1083/10000, Train Loss: 1.5768, Train Accuracy: 0.3795, Val Loss: 1.5787, Val Accuracy: 0.4018
Epoch 1084/10000, Train Loss: 1.5769, Train Accuracy: 0.3750, Val Loss: 1.5786, Val Accuracy: 0.4018
Epoch 1085/10000, Train Loss: 1.5763, Train Accuracy: 0.3672, Val Loss: 1.5786, Val Accuracy: 0.4018
Epoch 1086/10000, Train Loss: 1.5782, Train Accuracy: 0.3750, Val Loss: 1.5785, Val Accuracy: 0.4018
Epoch 1087/10000, Train Loss: 1.5757, Train Accuracy: 0.3761, Val Loss: 1.5784, Val Accuracy: 0.4018
Epoch 1088/10000, Train Loss: 1.5741, Train Accuracy: 0.3739, Val Loss: 1.5783, Val Accuracy: 0.4018
Epoch 1089/10000, Train Loss: 1.5764, Train Accuracy: 0.3661, Val Loss: 1.5782, Val Accuracy: 0.4018
Epoch 1090/10000, Train Loss: 1.5746, Train Accuracy: 0.3750, Val Loss: 1.5781, Val Accuracy: 0.4018
Epoch 1091/10000, Train Loss: 1.5752, Train Accuracy: 0.3694, Val Loss: 1.5781, Val Accuracy: 0.4018
Epoch 1092/10000, Train Loss: 1.5754, Train Accuracy: 0.3627, Val Loss: 1.5780, Val Accuracy: 0.4018
Epoch 1093/10000, Train Loss: 1.5758, Train Accuracy: 0.3571, Val Loss: 1.5779, Val Accuracy: 0.4018
Epoch 1094/10000, Train Loss: 1.5774, Train Accuracy: 0.3650, Val Loss: 1.5778, Val Accuracy: 0.4018
Epoch 1095/10000, Train Loss: 1.5749, Train Accuracy: 0.3783, Val Loss: 1.5777, Val Accuracy: 0.4018
Epoch 1096/10000, Train Loss: 1.5775, Train Accuracy: 0.3672, Val Loss: 1.5776, Val Accuracy: 0.4018
Epoch 1097/10000, Train Loss: 1.5737, Train Accuracy: 0.3694, Val Loss: 1.5776, Val Accuracy: 0.4018
Epoch 1098/10000, Train Loss: 1.5739, Train Accuracy: 0.3862, Val Loss: 1.5775, Val Accuracy: 0.4018
Epoch 1099/10000, Train Loss: 1.5734, Train Accuracy: 0.3672, Val Loss: 1.5774, Val Accuracy: 0.4062
Epoch 1100/10000, Train Loss: 1.5770, Train Accuracy: 0.3873, Val Loss: 1.5773, Val Accuracy: 0.4018
Epoch 1101/10000, Train Loss: 1.5736, Train Accuracy: 0.3683, Val Loss: 1.5772, Val Accuracy: 0.4062
Epoch 1102/10000, Train Loss: 1.5752, Train Accuracy: 0.3828, Val Loss: 1.5772, Val Accuracy: 0.4018
Epoch 1103/10000, Train Loss: 1.5755, Train Accuracy: 0.3929, Val Loss: 1.5771, Val Accuracy: 0.4062
Epoch 1104/10000, Train Loss: 1.5740, Train Accuracy: 0.3728, Val Loss: 1.5770, Val Accuracy: 0.4018
Epoch 1105/10000, Train Loss: 1.5742, Train Accuracy: 0.3906, Val Loss: 1.5769, Val Accuracy: 0.4018
Epoch 1106/10000, Train Loss: 1.5736, Train Accuracy: 0.3650, Val Loss: 1.5768, Val Accuracy: 0.4062
Epoch 1107/10000, Train Loss: 1.5765, Train Accuracy: 0.3594, Val Loss: 1.5767, Val Accuracy: 0.4062
Epoch 1108/10000, Train Loss: 1.5744, Train Accuracy: 0.3594, Val Loss: 1.5767, Val Accuracy: 0.4062
Epoch 1109/10000, Train Loss: 1.5756, Train Accuracy: 0.3705, Val Loss: 1.5766, Val Accuracy: 0.4062
Epoch 1110/10000, Train Loss: 1.5752, Train Accuracy: 0.3516, Val Loss: 1.5765, Val Accuracy: 0.4062
Epoch 1111/10000, Train Loss: 1.5728, Train Accuracy: 0.3806, Val Loss: 1.5764, Val Accuracy: 0.4018
Epoch 1112/10000, Train Loss: 1.5749, Train Accuracy: 0.3717, Val Loss: 1.5763, Val Accuracy: 0.4062
Epoch 1113/10000, Train Loss: 1.5731, Train Accuracy: 0.3739, Val Loss: 1.5762, Val Accuracy: 0.4062
Epoch 1114/10000, Train Loss: 1.5720, Train Accuracy: 0.3761, Val Loss: 1.5761, Val Accuracy: 0.4062
Epoch 1115/10000, Train Loss: 1.5728, Train Accuracy: 0.3895, Val Loss: 1.5760, Val Accuracy: 0.4062
Epoch 1116/10000, Train Loss: 1.5743, Train Accuracy: 0.3839, Val Loss: 1.5759, Val Accuracy: 0.4062
Epoch 1117/10000, Train Loss: 1.5729, Train Accuracy: 0.3605, Val Loss: 1.5758, Val Accuracy: 0.4062
Epoch 1118/10000, Train Loss: 1.5713, Train Accuracy: 0.3895, Val Loss: 1.5758, Val Accuracy: 0.4062
Epoch 1119/10000, Train Loss: 1.5731, Train Accuracy: 0.3783, Val Loss: 1.5757, Val Accuracy: 0.4062
Epoch 1120/10000, Train Loss: 1.5728, Train Accuracy: 0.3839, Val Loss: 1.5756, Val Accuracy: 0.4062
Epoch 1121/10000, Train Loss: 1.5743, Train Accuracy: 0.3750, Val Loss: 1.5755, Val Accuracy: 0.4062
Epoch 1122/10000, Train Loss: 1.5743, Train Accuracy: 0.3683, Val Loss: 1.5754, Val Accuracy: 0.4062
Epoch 1123/10000, Train Loss: 1.5735, Train Accuracy: 0.3772, Val Loss: 1.5753, Val Accuracy: 0.4062
Epoch 1124/10000, Train Loss: 1.5752, Train Accuracy: 0.3717, Val Loss: 1.5752, Val Accuracy: 0.4062
Epoch 1125/10000, Train Loss: 1.5720, Train Accuracy: 0.3895, Val Loss: 1.5751, Val Accuracy: 0.4062
Epoch 1126/10000, Train Loss: 1.5736, Train Accuracy: 0.3705, Val Loss: 1.5751, Val Accuracy: 0.4062
Epoch 1127/10000, Train Loss: 1.5724, Train Accuracy: 0.3817, Val Loss: 1.5750, Val Accuracy: 0.4062
Epoch 1128/10000, Train Loss: 1.5702, Train Accuracy: 0.3772, Val Loss: 1.5749, Val Accuracy: 0.4062
Epoch 1129/10000, Train Loss: 1.5732, Train Accuracy: 0.3694, Val Loss: 1.5748, Val Accuracy: 0.4062
Epoch 1130/10000, Train Loss: 1.5686, Train Accuracy: 0.3862, Val Loss: 1.5747, Val Accuracy: 0.4062
Epoch 1131/10000, Train Loss: 1.5718, Train Accuracy: 0.3772, Val Loss: 1.5747, Val Accuracy: 0.4107
Epoch 1132/10000, Train Loss: 1.5727, Train Accuracy: 0.3806, Val Loss: 1.5745, Val Accuracy: 0.4107
Epoch 1133/10000, Train Loss: 1.5723, Train Accuracy: 0.3627, Val Loss: 1.5745, Val Accuracy: 0.4107
Epoch 1134/10000, Train Loss: 1.5744, Train Accuracy: 0.3705, Val Loss: 1.5744, Val Accuracy: 0.4107
Epoch 1135/10000, Train Loss: 1.5710, Train Accuracy: 0.4062, Val Loss: 1.5743, Val Accuracy: 0.4107
Epoch 1136/10000, Train Loss: 1.5696, Train Accuracy: 0.3828, Val Loss: 1.5742, Val Accuracy: 0.4107
Epoch 1137/10000, Train Loss: 1.5713, Train Accuracy: 0.3806, Val Loss: 1.5741, Val Accuracy: 0.4107
Epoch 1138/10000, Train Loss: 1.5712, Train Accuracy: 0.3884, Val Loss: 1.5740, Val Accuracy: 0.4107
Epoch 1139/10000, Train Loss: 1.5700, Train Accuracy: 0.3795, Val Loss: 1.5739, Val Accuracy: 0.4107
Epoch 1140/10000, Train Loss: 1.5707, Train Accuracy: 0.3761, Val Loss: 1.5738, Val Accuracy: 0.4107
Epoch 1141/10000, Train Loss: 1.5710, Train Accuracy: 0.3884, Val Loss: 1.5737, Val Accuracy: 0.4107
Epoch 1142/10000, Train Loss: 1.5689, Train Accuracy: 0.3806, Val Loss: 1.5736, Val Accuracy: 0.4107
Epoch 1143/10000, Train Loss: 1.5706, Train Accuracy: 0.3828, Val Loss: 1.5736, Val Accuracy: 0.4107
Epoch 1144/10000, Train Loss: 1.5722, Train Accuracy: 0.3560, Val Loss: 1.5735, Val Accuracy: 0.4107
Epoch 1145/10000, Train Loss: 1.5704, Train Accuracy: 0.3795, Val Loss: 1.5734, Val Accuracy: 0.4107
Epoch 1146/10000, Train Loss: 1.5715, Train Accuracy: 0.3817, Val Loss: 1.5733, Val Accuracy: 0.4107
Epoch 1147/10000, Train Loss: 1.5699, Train Accuracy: 0.3783, Val Loss: 1.5732, Val Accuracy: 0.4107
Epoch 1148/10000, Train Loss: 1.5727, Train Accuracy: 0.3895, Val Loss: 1.5731, Val Accuracy: 0.4107
Epoch 1149/10000, Train Loss: 1.5711, Train Accuracy: 0.3705, Val Loss: 1.5730, Val Accuracy: 0.4107
Epoch 1150/10000, Train Loss: 1.5721, Train Accuracy: 0.3862, Val Loss: 1.5729, Val Accuracy: 0.4062
Epoch 1151/10000, Train Loss: 1.5684, Train Accuracy: 0.3917, Val Loss: 1.5728, Val Accuracy: 0.4062
Epoch 1152/10000, Train Loss: 1.5668, Train Accuracy: 0.3761, Val Loss: 1.5727, Val Accuracy: 0.4062
Epoch 1153/10000, Train Loss: 1.5717, Train Accuracy: 0.3616, Val Loss: 1.5726, Val Accuracy: 0.4062
Epoch 1154/10000, Train Loss: 1.5694, Train Accuracy: 0.4018, Val Loss: 1.5725, Val Accuracy: 0.4062
Epoch 1155/10000, Train Loss: 1.5679, Train Accuracy: 0.3973, Val Loss: 1.5724, Val Accuracy: 0.4062
Epoch 1156/10000, Train Loss: 1.5687, Train Accuracy: 0.3728, Val Loss: 1.5723, Val Accuracy: 0.4062
Epoch 1157/10000, Train Loss: 1.5684, Train Accuracy: 0.3728, Val Loss: 1.5722, Val Accuracy: 0.4062
Epoch 1158/10000, Train Loss: 1.5697, Train Accuracy: 0.3806, Val Loss: 1.5721, Val Accuracy: 0.4062
Epoch 1159/10000, Train Loss: 1.5716, Train Accuracy: 0.3717, Val Loss: 1.5720, Val Accuracy: 0.4062
Epoch 1160/10000, Train Loss: 1.5708, Train Accuracy: 0.3817, Val Loss: 1.5719, Val Accuracy: 0.4062
Epoch 1161/10000, Train Loss: 1.5706, Train Accuracy: 0.3750, Val Loss: 1.5718, Val Accuracy: 0.4062
Epoch 1162/10000, Train Loss: 1.5690, Train Accuracy: 0.3873, Val Loss: 1.5717, Val Accuracy: 0.4062
Epoch 1163/10000, Train Loss: 1.5695, Train Accuracy: 0.3694, Val Loss: 1.5717, Val Accuracy: 0.4062
Epoch 1164/10000, Train Loss: 1.5671, Train Accuracy: 0.4007, Val Loss: 1.5716, Val Accuracy: 0.4062
Epoch 1165/10000, Train Loss: 1.5684, Train Accuracy: 0.3929, Val Loss: 1.5715, Val Accuracy: 0.4062
Epoch 1166/10000, Train Loss: 1.5687, Train Accuracy: 0.3828, Val Loss: 1.5714, Val Accuracy: 0.4062
Epoch 1167/10000, Train Loss: 1.5718, Train Accuracy: 0.3661, Val Loss: 1.5713, Val Accuracy: 0.4062
Epoch 1168/10000, Train Loss: 1.5682, Train Accuracy: 0.3951, Val Loss: 1.5711, Val Accuracy: 0.4062
Epoch 1169/10000, Train Loss: 1.5706, Train Accuracy: 0.3638, Val Loss: 1.5711, Val Accuracy: 0.4062
Epoch 1170/10000, Train Loss: 1.5683, Train Accuracy: 0.3895, Val Loss: 1.5710, Val Accuracy: 0.4062
Epoch 1171/10000, Train Loss: 1.5697, Train Accuracy: 0.3739, Val Loss: 1.5708, Val Accuracy: 0.4062
Epoch 1172/10000, Train Loss: 1.5686, Train Accuracy: 0.3973, Val Loss: 1.5708, Val Accuracy: 0.4062
Epoch 1173/10000, Train Loss: 1.5691, Train Accuracy: 0.3873, Val Loss: 1.5707, Val Accuracy: 0.4062
Epoch 1174/10000, Train Loss: 1.5703, Train Accuracy: 0.3772, Val Loss: 1.5706, Val Accuracy: 0.4062
Epoch 1175/10000, Train Loss: 1.5686, Train Accuracy: 0.3638, Val Loss: 1.5705, Val Accuracy: 0.4062
Epoch 1176/10000, Train Loss: 1.5654, Train Accuracy: 0.3761, Val Loss: 1.5704, Val Accuracy: 0.4107
Epoch 1177/10000, Train Loss: 1.5648, Train Accuracy: 0.3906, Val Loss: 1.5703, Val Accuracy: 0.4062
Epoch 1178/10000, Train Loss: 1.5686, Train Accuracy: 0.3717, Val Loss: 1.5702, Val Accuracy: 0.4107
Epoch 1179/10000, Train Loss: 1.5672, Train Accuracy: 0.3761, Val Loss: 1.5701, Val Accuracy: 0.4062
Epoch 1180/10000, Train Loss: 1.5669, Train Accuracy: 0.3783, Val Loss: 1.5700, Val Accuracy: 0.4107
Epoch 1181/10000, Train Loss: 1.5675, Train Accuracy: 0.3739, Val Loss: 1.5699, Val Accuracy: 0.4107
Epoch 1182/10000, Train Loss: 1.5672, Train Accuracy: 0.3828, Val Loss: 1.5698, Val Accuracy: 0.4107
Epoch 1183/10000, Train Loss: 1.5662, Train Accuracy: 0.3895, Val Loss: 1.5697, Val Accuracy: 0.4107
Epoch 1184/10000, Train Loss: 1.5680, Train Accuracy: 0.3839, Val Loss: 1.5696, Val Accuracy: 0.4107
Epoch 1185/10000, Train Loss: 1.5658, Train Accuracy: 0.3895, Val Loss: 1.5695, Val Accuracy: 0.4107
Epoch 1186/10000, Train Loss: 1.5665, Train Accuracy: 0.3694, Val Loss: 1.5694, Val Accuracy: 0.4107
Epoch 1187/10000, Train Loss: 1.5677, Train Accuracy: 0.3683, Val Loss: 1.5693, Val Accuracy: 0.4107
Epoch 1188/10000, Train Loss: 1.5685, Train Accuracy: 0.3638, Val Loss: 1.5692, Val Accuracy: 0.4107
Epoch 1189/10000, Train Loss: 1.5664, Train Accuracy: 0.3862, Val Loss: 1.5691, Val Accuracy: 0.4107
Epoch 1190/10000, Train Loss: 1.5638, Train Accuracy: 0.4051, Val Loss: 1.5690, Val Accuracy: 0.4107
Epoch 1191/10000, Train Loss: 1.5657, Train Accuracy: 0.3895, Val Loss: 1.5689, Val Accuracy: 0.4107
Epoch 1192/10000, Train Loss: 1.5670, Train Accuracy: 0.3873, Val Loss: 1.5688, Val Accuracy: 0.4107
Epoch 1193/10000, Train Loss: 1.5668, Train Accuracy: 0.3817, Val Loss: 1.5687, Val Accuracy: 0.4107
Epoch 1194/10000, Train Loss: 1.5650, Train Accuracy: 0.3839, Val Loss: 1.5686, Val Accuracy: 0.4107
Epoch 1195/10000, Train Loss: 1.5651, Train Accuracy: 0.3850, Val Loss: 1.5684, Val Accuracy: 0.4152
Epoch 1196/10000, Train Loss: 1.5649, Train Accuracy: 0.3940, Val Loss: 1.5683, Val Accuracy: 0.4107
Epoch 1197/10000, Train Loss: 1.5669, Train Accuracy: 0.3884, Val Loss: 1.5682, Val Accuracy: 0.4107
Epoch 1198/10000, Train Loss: 1.5663, Train Accuracy: 0.3873, Val Loss: 1.5681, Val Accuracy: 0.4107
Epoch 1199/10000, Train Loss: 1.5656, Train Accuracy: 0.3839, Val Loss: 1.5680, Val Accuracy: 0.4107
Epoch 1200/10000, Train Loss: 1.5660, Train Accuracy: 0.3739, Val Loss: 1.5679, Val Accuracy: 0.4107
Epoch 1201/10000, Train Loss: 1.5682, Train Accuracy: 0.3728, Val Loss: 1.5678, Val Accuracy: 0.4107
Epoch 1202/10000, Train Loss: 1.5613, Train Accuracy: 0.3984, Val Loss: 1.5677, Val Accuracy: 0.4107
Epoch 1203/10000, Train Loss: 1.5678, Train Accuracy: 0.3817, Val Loss: 1.5676, Val Accuracy: 0.4152
Epoch 1204/10000, Train Loss: 1.5643, Train Accuracy: 0.3929, Val Loss: 1.5675, Val Accuracy: 0.4107
Epoch 1205/10000, Train Loss: 1.5625, Train Accuracy: 0.3873, Val Loss: 1.5674, Val Accuracy: 0.4152
Epoch 1206/10000, Train Loss: 1.5647, Train Accuracy: 0.3761, Val Loss: 1.5673, Val Accuracy: 0.4107
Epoch 1207/10000, Train Loss: 1.5630, Train Accuracy: 0.3884, Val Loss: 1.5671, Val Accuracy: 0.4152
Epoch 1208/10000, Train Loss: 1.5620, Train Accuracy: 0.3906, Val Loss: 1.5670, Val Accuracy: 0.4152
Epoch 1209/10000, Train Loss: 1.5630, Train Accuracy: 0.3962, Val Loss: 1.5669, Val Accuracy: 0.4152
Epoch 1210/10000, Train Loss: 1.5635, Train Accuracy: 0.4007, Val Loss: 1.5667, Val Accuracy: 0.4152
Epoch 1211/10000, Train Loss: 1.5648, Train Accuracy: 0.3873, Val Loss: 1.5666, Val Accuracy: 0.4152
Epoch 1212/10000, Train Loss: 1.5626, Train Accuracy: 0.4051, Val Loss: 1.5665, Val Accuracy: 0.4152
Epoch 1213/10000, Train Loss: 1.5642, Train Accuracy: 0.3772, Val Loss: 1.5664, Val Accuracy: 0.4152
Epoch 1214/10000, Train Loss: 1.5643, Train Accuracy: 0.3783, Val Loss: 1.5663, Val Accuracy: 0.4152
Epoch 1215/10000, Train Loss: 1.5632, Train Accuracy: 0.3951, Val Loss: 1.5662, Val Accuracy: 0.4152
Epoch 1216/10000, Train Loss: 1.5665, Train Accuracy: 0.3795, Val Loss: 1.5661, Val Accuracy: 0.4152
Epoch 1217/10000, Train Loss: 1.5632, Train Accuracy: 0.3951, Val Loss: 1.5659, Val Accuracy: 0.4107
Epoch 1218/10000, Train Loss: 1.5636, Train Accuracy: 0.3828, Val Loss: 1.5658, Val Accuracy: 0.4107
Epoch 1219/10000, Train Loss: 1.5625, Train Accuracy: 0.4085, Val Loss: 1.5657, Val Accuracy: 0.4107
Epoch 1220/10000, Train Loss: 1.5624, Train Accuracy: 0.3783, Val Loss: 1.5656, Val Accuracy: 0.4107
Epoch 1221/10000, Train Loss: 1.5644, Train Accuracy: 0.3828, Val Loss: 1.5655, Val Accuracy: 0.4107
Epoch 1222/10000, Train Loss: 1.5609, Train Accuracy: 0.3772, Val Loss: 1.5654, Val Accuracy: 0.4107
Epoch 1223/10000, Train Loss: 1.5626, Train Accuracy: 0.3806, Val Loss: 1.5652, Val Accuracy: 0.4152
Epoch 1224/10000, Train Loss: 1.5639, Train Accuracy: 0.3783, Val Loss: 1.5651, Val Accuracy: 0.4196
Epoch 1225/10000, Train Loss: 1.5623, Train Accuracy: 0.3850, Val Loss: 1.5650, Val Accuracy: 0.4196
Epoch 1226/10000, Train Loss: 1.5603, Train Accuracy: 0.3895, Val Loss: 1.5649, Val Accuracy: 0.4196
Epoch 1227/10000, Train Loss: 1.5617, Train Accuracy: 0.3884, Val Loss: 1.5647, Val Accuracy: 0.4196
Epoch 1228/10000, Train Loss: 1.5611, Train Accuracy: 0.3839, Val Loss: 1.5647, Val Accuracy: 0.4196
Epoch 1229/10000, Train Loss: 1.5631, Train Accuracy: 0.3973, Val Loss: 1.5645, Val Accuracy: 0.4196
Epoch 1230/10000, Train Loss: 1.5634, Train Accuracy: 0.3493, Val Loss: 1.5645, Val Accuracy: 0.4196
Epoch 1231/10000, Train Loss: 1.5596, Train Accuracy: 0.3996, Val Loss: 1.5644, Val Accuracy: 0.4196
Epoch 1232/10000, Train Loss: 1.5610, Train Accuracy: 0.3761, Val Loss: 1.5642, Val Accuracy: 0.4196
Epoch 1233/10000, Train Loss: 1.5632, Train Accuracy: 0.3661, Val Loss: 1.5641, Val Accuracy: 0.4196
Epoch 1234/10000, Train Loss: 1.5610, Train Accuracy: 0.3984, Val Loss: 1.5640, Val Accuracy: 0.4152
Epoch 1235/10000, Train Loss: 1.5621, Train Accuracy: 0.3862, Val Loss: 1.5638, Val Accuracy: 0.4152
Epoch 1236/10000, Train Loss: 1.5615, Train Accuracy: 0.3906, Val Loss: 1.5637, Val Accuracy: 0.4152
Epoch 1237/10000, Train Loss: 1.5611, Train Accuracy: 0.3817, Val Loss: 1.5636, Val Accuracy: 0.4152
Epoch 1238/10000, Train Loss: 1.5617, Train Accuracy: 0.3817, Val Loss: 1.5635, Val Accuracy: 0.4152
Epoch 1239/10000, Train Loss: 1.5585, Train Accuracy: 0.3917, Val Loss: 1.5633, Val Accuracy: 0.4152
Epoch 1240/10000, Train Loss: 1.5601, Train Accuracy: 0.4029, Val Loss: 1.5632, Val Accuracy: 0.4196
Epoch 1241/10000, Train Loss: 1.5596, Train Accuracy: 0.3817, Val Loss: 1.5631, Val Accuracy: 0.4196
Epoch 1242/10000, Train Loss: 1.5592, Train Accuracy: 0.3984, Val Loss: 1.5630, Val Accuracy: 0.4241
Epoch 1243/10000, Train Loss: 1.5620, Train Accuracy: 0.3772, Val Loss: 1.5629, Val Accuracy: 0.4241
Epoch 1244/10000, Train Loss: 1.5602, Train Accuracy: 0.3817, Val Loss: 1.5627, Val Accuracy: 0.4241
Epoch 1245/10000, Train Loss: 1.5601, Train Accuracy: 0.3906, Val Loss: 1.5626, Val Accuracy: 0.4196
Epoch 1246/10000, Train Loss: 1.5592, Train Accuracy: 0.3862, Val Loss: 1.5625, Val Accuracy: 0.4196
Epoch 1247/10000, Train Loss: 1.5590, Train Accuracy: 0.4141, Val Loss: 1.5624, Val Accuracy: 0.4196
Epoch 1248/10000, Train Loss: 1.5586, Train Accuracy: 0.3895, Val Loss: 1.5623, Val Accuracy: 0.4196
Epoch 1249/10000, Train Loss: 1.5581, Train Accuracy: 0.3862, Val Loss: 1.5621, Val Accuracy: 0.4241
Epoch 1250/10000, Train Loss: 1.5596, Train Accuracy: 0.4029, Val Loss: 1.5620, Val Accuracy: 0.4241
Epoch 1251/10000, Train Loss: 1.5600, Train Accuracy: 0.3873, Val Loss: 1.5619, Val Accuracy: 0.4241
Epoch 1252/10000, Train Loss: 1.5582, Train Accuracy: 0.3694, Val Loss: 1.5618, Val Accuracy: 0.4241
Epoch 1253/10000, Train Loss: 1.5577, Train Accuracy: 0.3884, Val Loss: 1.5617, Val Accuracy: 0.4241
Epoch 1254/10000, Train Loss: 1.5573, Train Accuracy: 0.4074, Val Loss: 1.5616, Val Accuracy: 0.4241
Epoch 1255/10000, Train Loss: 1.5602, Train Accuracy: 0.3884, Val Loss: 1.5614, Val Accuracy: 0.4241
Epoch 1256/10000, Train Loss: 1.5589, Train Accuracy: 0.3850, Val Loss: 1.5613, Val Accuracy: 0.4241
Epoch 1257/10000, Train Loss: 1.5564, Train Accuracy: 0.4163, Val Loss: 1.5612, Val Accuracy: 0.4196
Epoch 1258/10000, Train Loss: 1.5590, Train Accuracy: 0.3895, Val Loss: 1.5611, Val Accuracy: 0.4196
Epoch 1259/10000, Train Loss: 1.5559, Train Accuracy: 0.4141, Val Loss: 1.5609, Val Accuracy: 0.4241
Epoch 1260/10000, Train Loss: 1.5582, Train Accuracy: 0.3940, Val Loss: 1.5608, Val Accuracy: 0.4241
Epoch 1261/10000, Train Loss: 1.5573, Train Accuracy: 0.4018, Val Loss: 1.5607, Val Accuracy: 0.4241
Epoch 1262/10000, Train Loss: 1.5558, Train Accuracy: 0.4040, Val Loss: 1.5605, Val Accuracy: 0.4241
Epoch 1263/10000, Train Loss: 1.5574, Train Accuracy: 0.3962, Val Loss: 1.5604, Val Accuracy: 0.4241
Epoch 1264/10000, Train Loss: 1.5604, Train Accuracy: 0.3917, Val Loss: 1.5603, Val Accuracy: 0.4241
Epoch 1265/10000, Train Loss: 1.5531, Train Accuracy: 0.3962, Val Loss: 1.5602, Val Accuracy: 0.4286
Epoch 1266/10000, Train Loss: 1.5599, Train Accuracy: 0.3917, Val Loss: 1.5600, Val Accuracy: 0.4241
Epoch 1267/10000, Train Loss: 1.5584, Train Accuracy: 0.3951, Val Loss: 1.5599, Val Accuracy: 0.4196
Epoch 1268/10000, Train Loss: 1.5556, Train Accuracy: 0.3996, Val Loss: 1.5598, Val Accuracy: 0.4196
Epoch 1269/10000, Train Loss: 1.5577, Train Accuracy: 0.4029, Val Loss: 1.5597, Val Accuracy: 0.4196
Epoch 1270/10000, Train Loss: 1.5552, Train Accuracy: 0.3884, Val Loss: 1.5596, Val Accuracy: 0.4196
Epoch 1271/10000, Train Loss: 1.5570, Train Accuracy: 0.4062, Val Loss: 1.5595, Val Accuracy: 0.4196
Epoch 1272/10000, Train Loss: 1.5598, Train Accuracy: 0.3839, Val Loss: 1.5594, Val Accuracy: 0.4196
Epoch 1273/10000, Train Loss: 1.5572, Train Accuracy: 0.4062, Val Loss: 1.5592, Val Accuracy: 0.4196
Epoch 1274/10000, Train Loss: 1.5577, Train Accuracy: 0.3895, Val Loss: 1.5591, Val Accuracy: 0.4196
Epoch 1275/10000, Train Loss: 1.5551, Train Accuracy: 0.3951, Val Loss: 1.5590, Val Accuracy: 0.4196
Epoch 1276/10000, Train Loss: 1.5568, Train Accuracy: 0.3973, Val Loss: 1.5588, Val Accuracy: 0.4196
Epoch 1277/10000, Train Loss: 1.5555, Train Accuracy: 0.3873, Val Loss: 1.5587, Val Accuracy: 0.4196
Epoch 1278/10000, Train Loss: 1.5553, Train Accuracy: 0.4129, Val Loss: 1.5586, Val Accuracy: 0.4196
Epoch 1279/10000, Train Loss: 1.5544, Train Accuracy: 0.3940, Val Loss: 1.5584, Val Accuracy: 0.4286
Epoch 1280/10000, Train Loss: 1.5539, Train Accuracy: 0.3828, Val Loss: 1.5583, Val Accuracy: 0.4196
Epoch 1281/10000, Train Loss: 1.5557, Train Accuracy: 0.3940, Val Loss: 1.5582, Val Accuracy: 0.4286
Epoch 1282/10000, Train Loss: 1.5573, Train Accuracy: 0.3873, Val Loss: 1.5580, Val Accuracy: 0.4286
Epoch 1283/10000, Train Loss: 1.5548, Train Accuracy: 0.4096, Val Loss: 1.5579, Val Accuracy: 0.4286
Epoch 1284/10000, Train Loss: 1.5560, Train Accuracy: 0.4040, Val Loss: 1.5577, Val Accuracy: 0.4286
Epoch 1285/10000, Train Loss: 1.5527, Train Accuracy: 0.3951, Val Loss: 1.5576, Val Accuracy: 0.4286
Epoch 1286/10000, Train Loss: 1.5558, Train Accuracy: 0.3984, Val Loss: 1.5575, Val Accuracy: 0.4286
Epoch 1287/10000, Train Loss: 1.5559, Train Accuracy: 0.3951, Val Loss: 1.5573, Val Accuracy: 0.4330
Epoch 1288/10000, Train Loss: 1.5537, Train Accuracy: 0.4018, Val Loss: 1.5572, Val Accuracy: 0.4286
Epoch 1289/10000, Train Loss: 1.5565, Train Accuracy: 0.3795, Val Loss: 1.5571, Val Accuracy: 0.4286
Epoch 1290/10000, Train Loss: 1.5546, Train Accuracy: 0.3973, Val Loss: 1.5569, Val Accuracy: 0.4330
Epoch 1291/10000, Train Loss: 1.5546, Train Accuracy: 0.3828, Val Loss: 1.5568, Val Accuracy: 0.4286
Epoch 1292/10000, Train Loss: 1.5513, Train Accuracy: 0.4129, Val Loss: 1.5567, Val Accuracy: 0.4286
Epoch 1293/10000, Train Loss: 1.5549, Train Accuracy: 0.3873, Val Loss: 1.5566, Val Accuracy: 0.4286
Epoch 1294/10000, Train Loss: 1.5525, Train Accuracy: 0.3996, Val Loss: 1.5564, Val Accuracy: 0.4286
Epoch 1295/10000, Train Loss: 1.5504, Train Accuracy: 0.3940, Val Loss: 1.5563, Val Accuracy: 0.4286
Epoch 1296/10000, Train Loss: 1.5530, Train Accuracy: 0.4029, Val Loss: 1.5562, Val Accuracy: 0.4286
Epoch 1297/10000, Train Loss: 1.5532, Train Accuracy: 0.3862, Val Loss: 1.5560, Val Accuracy: 0.4241
Epoch 1298/10000, Train Loss: 1.5566, Train Accuracy: 0.3940, Val Loss: 1.5559, Val Accuracy: 0.4241
Epoch 1299/10000, Train Loss: 1.5522, Train Accuracy: 0.4040, Val Loss: 1.5557, Val Accuracy: 0.4286
Epoch 1300/10000, Train Loss: 1.5509, Train Accuracy: 0.3884, Val Loss: 1.5556, Val Accuracy: 0.4286
Epoch 1301/10000, Train Loss: 1.5500, Train Accuracy: 0.4196, Val Loss: 1.5554, Val Accuracy: 0.4241
Epoch 1302/10000, Train Loss: 1.5526, Train Accuracy: 0.3850, Val Loss: 1.5553, Val Accuracy: 0.4241
Epoch 1303/10000, Train Loss: 1.5531, Train Accuracy: 0.3828, Val Loss: 1.5551, Val Accuracy: 0.4241
Epoch 1304/10000, Train Loss: 1.5554, Train Accuracy: 0.3962, Val Loss: 1.5550, Val Accuracy: 0.4241
Epoch 1305/10000, Train Loss: 1.5526, Train Accuracy: 0.3895, Val Loss: 1.5549, Val Accuracy: 0.4241
Epoch 1306/10000, Train Loss: 1.5517, Train Accuracy: 0.4018, Val Loss: 1.5547, Val Accuracy: 0.4241
Epoch 1307/10000, Train Loss: 1.5533, Train Accuracy: 0.4096, Val Loss: 1.5546, Val Accuracy: 0.4241
Epoch 1308/10000, Train Loss: 1.5510, Train Accuracy: 0.4007, Val Loss: 1.5545, Val Accuracy: 0.4241
Epoch 1309/10000, Train Loss: 1.5535, Train Accuracy: 0.3862, Val Loss: 1.5543, Val Accuracy: 0.4241
Epoch 1310/10000, Train Loss: 1.5501, Train Accuracy: 0.4096, Val Loss: 1.5542, Val Accuracy: 0.4241
Epoch 1311/10000, Train Loss: 1.5534, Train Accuracy: 0.3951, Val Loss: 1.5541, Val Accuracy: 0.4241
Epoch 1312/10000, Train Loss: 1.5516, Train Accuracy: 0.4062, Val Loss: 1.5540, Val Accuracy: 0.4196
Epoch 1313/10000, Train Loss: 1.5492, Train Accuracy: 0.4196, Val Loss: 1.5538, Val Accuracy: 0.4241
Epoch 1314/10000, Train Loss: 1.5508, Train Accuracy: 0.3940, Val Loss: 1.5537, Val Accuracy: 0.4241
Epoch 1315/10000, Train Loss: 1.5525, Train Accuracy: 0.4007, Val Loss: 1.5535, Val Accuracy: 0.4241
Epoch 1316/10000, Train Loss: 1.5503, Train Accuracy: 0.4018, Val Loss: 1.5534, Val Accuracy: 0.4241
Epoch 1317/10000, Train Loss: 1.5506, Train Accuracy: 0.3984, Val Loss: 1.5533, Val Accuracy: 0.4241
Epoch 1318/10000, Train Loss: 1.5523, Train Accuracy: 0.3895, Val Loss: 1.5531, Val Accuracy: 0.4196
Epoch 1319/10000, Train Loss: 1.5516, Train Accuracy: 0.4007, Val Loss: 1.5530, Val Accuracy: 0.4241
Epoch 1320/10000, Train Loss: 1.5521, Train Accuracy: 0.3906, Val Loss: 1.5528, Val Accuracy: 0.4196
Epoch 1321/10000, Train Loss: 1.5514, Train Accuracy: 0.3806, Val Loss: 1.5527, Val Accuracy: 0.4196
Epoch 1322/10000, Train Loss: 1.5505, Train Accuracy: 0.4085, Val Loss: 1.5526, Val Accuracy: 0.4196
Epoch 1323/10000, Train Loss: 1.5516, Train Accuracy: 0.3739, Val Loss: 1.5525, Val Accuracy: 0.4196
Epoch 1324/10000, Train Loss: 1.5506, Train Accuracy: 0.3984, Val Loss: 1.5524, Val Accuracy: 0.4196
Epoch 1325/10000, Train Loss: 1.5504, Train Accuracy: 0.4007, Val Loss: 1.5523, Val Accuracy: 0.4196
Epoch 1326/10000, Train Loss: 1.5506, Train Accuracy: 0.3929, Val Loss: 1.5521, Val Accuracy: 0.4196
Epoch 1327/10000, Train Loss: 1.5518, Train Accuracy: 0.3750, Val Loss: 1.5520, Val Accuracy: 0.4196
Epoch 1328/10000, Train Loss: 1.5480, Train Accuracy: 0.3895, Val Loss: 1.5518, Val Accuracy: 0.4196
Epoch 1329/10000, Train Loss: 1.5493, Train Accuracy: 0.3884, Val Loss: 1.5517, Val Accuracy: 0.4196
Epoch 1330/10000, Train Loss: 1.5480, Train Accuracy: 0.4174, Val Loss: 1.5515, Val Accuracy: 0.4196
Epoch 1331/10000, Train Loss: 1.5469, Train Accuracy: 0.4174, Val Loss: 1.5514, Val Accuracy: 0.4241
Epoch 1332/10000, Train Loss: 1.5501, Train Accuracy: 0.4029, Val Loss: 1.5512, Val Accuracy: 0.4241
Epoch 1333/10000, Train Loss: 1.5491, Train Accuracy: 0.4152, Val Loss: 1.5510, Val Accuracy: 0.4241
Epoch 1334/10000, Train Loss: 1.5450, Train Accuracy: 0.4118, Val Loss: 1.5509, Val Accuracy: 0.4196
Epoch 1335/10000, Train Loss: 1.5465, Train Accuracy: 0.3940, Val Loss: 1.5508, Val Accuracy: 0.4196
Epoch 1336/10000, Train Loss: 1.5479, Train Accuracy: 0.3783, Val Loss: 1.5506, Val Accuracy: 0.4196
Epoch 1337/10000, Train Loss: 1.5484, Train Accuracy: 0.3996, Val Loss: 1.5505, Val Accuracy: 0.4152
Epoch 1338/10000, Train Loss: 1.5451, Train Accuracy: 0.3929, Val Loss: 1.5503, Val Accuracy: 0.4152
Epoch 1339/10000, Train Loss: 1.5491, Train Accuracy: 0.3906, Val Loss: 1.5501, Val Accuracy: 0.4152
Epoch 1340/10000, Train Loss: 1.5483, Train Accuracy: 0.4007, Val Loss: 1.5499, Val Accuracy: 0.4152
Epoch 1341/10000, Train Loss: 1.5474, Train Accuracy: 0.4029, Val Loss: 1.5498, Val Accuracy: 0.4152
Epoch 1342/10000, Train Loss: 1.5460, Train Accuracy: 0.3906, Val Loss: 1.5497, Val Accuracy: 0.4152
Epoch 1343/10000, Train Loss: 1.5496, Train Accuracy: 0.3895, Val Loss: 1.5495, Val Accuracy: 0.4152
Epoch 1344/10000, Train Loss: 1.5479, Train Accuracy: 0.3839, Val Loss: 1.5494, Val Accuracy: 0.4152
Epoch 1345/10000, Train Loss: 1.5474, Train Accuracy: 0.3817, Val Loss: 1.5492, Val Accuracy: 0.4152
Epoch 1346/10000, Train Loss: 1.5488, Train Accuracy: 0.4029, Val Loss: 1.5491, Val Accuracy: 0.4107
Epoch 1347/10000, Train Loss: 1.5454, Train Accuracy: 0.4040, Val Loss: 1.5490, Val Accuracy: 0.4107
Epoch 1348/10000, Train Loss: 1.5480, Train Accuracy: 0.3940, Val Loss: 1.5488, Val Accuracy: 0.4107
Epoch 1349/10000, Train Loss: 1.5472, Train Accuracy: 0.4029, Val Loss: 1.5487, Val Accuracy: 0.4107
Epoch 1350/10000, Train Loss: 1.5446, Train Accuracy: 0.4129, Val Loss: 1.5485, Val Accuracy: 0.4107
Epoch 1351/10000, Train Loss: 1.5483, Train Accuracy: 0.3884, Val Loss: 1.5484, Val Accuracy: 0.4107
Epoch 1352/10000, Train Loss: 1.5452, Train Accuracy: 0.3973, Val Loss: 1.5482, Val Accuracy: 0.4062
Epoch 1353/10000, Train Loss: 1.5465, Train Accuracy: 0.3895, Val Loss: 1.5481, Val Accuracy: 0.4062
Epoch 1354/10000, Train Loss: 1.5457, Train Accuracy: 0.4096, Val Loss: 1.5479, Val Accuracy: 0.4062
Epoch 1355/10000, Train Loss: 1.5455, Train Accuracy: 0.3839, Val Loss: 1.5478, Val Accuracy: 0.4062
Epoch 1356/10000, Train Loss: 1.5459, Train Accuracy: 0.4129, Val Loss: 1.5476, Val Accuracy: 0.4062
Epoch 1357/10000, Train Loss: 1.5465, Train Accuracy: 0.4040, Val Loss: 1.5475, Val Accuracy: 0.4062
Epoch 1358/10000, Train Loss: 1.5439, Train Accuracy: 0.4051, Val Loss: 1.5474, Val Accuracy: 0.4062
Epoch 1359/10000, Train Loss: 1.5454, Train Accuracy: 0.3973, Val Loss: 1.5471, Val Accuracy: 0.4062
Epoch 1360/10000, Train Loss: 1.5441, Train Accuracy: 0.3806, Val Loss: 1.5470, Val Accuracy: 0.4018
Epoch 1361/10000, Train Loss: 1.5468, Train Accuracy: 0.4141, Val Loss: 1.5469, Val Accuracy: 0.4062
Epoch 1362/10000, Train Loss: 1.5425, Train Accuracy: 0.4029, Val Loss: 1.5467, Val Accuracy: 0.4018
Epoch 1363/10000, Train Loss: 1.5472, Train Accuracy: 0.3862, Val Loss: 1.5466, Val Accuracy: 0.4018
Epoch 1364/10000, Train Loss: 1.5459, Train Accuracy: 0.3906, Val Loss: 1.5464, Val Accuracy: 0.4018
Epoch 1365/10000, Train Loss: 1.5415, Train Accuracy: 0.4085, Val Loss: 1.5462, Val Accuracy: 0.4018
Epoch 1366/10000, Train Loss: 1.5429, Train Accuracy: 0.4275, Val Loss: 1.5461, Val Accuracy: 0.4018
Epoch 1367/10000, Train Loss: 1.5436, Train Accuracy: 0.4185, Val Loss: 1.5460, Val Accuracy: 0.4018
Epoch 1368/10000, Train Loss: 1.5414, Train Accuracy: 0.4275, Val Loss: 1.5457, Val Accuracy: 0.4018
Epoch 1369/10000, Train Loss: 1.5431, Train Accuracy: 0.4118, Val Loss: 1.5456, Val Accuracy: 0.4062
Epoch 1370/10000, Train Loss: 1.5432, Train Accuracy: 0.4074, Val Loss: 1.5455, Val Accuracy: 0.4062
Epoch 1371/10000, Train Loss: 1.5434, Train Accuracy: 0.4029, Val Loss: 1.5454, Val Accuracy: 0.4062
Epoch 1372/10000, Train Loss: 1.5425, Train Accuracy: 0.4029, Val Loss: 1.5452, Val Accuracy: 0.4062
Epoch 1373/10000, Train Loss: 1.5418, Train Accuracy: 0.4040, Val Loss: 1.5451, Val Accuracy: 0.4062
Epoch 1374/10000, Train Loss: 1.5413, Train Accuracy: 0.3917, Val Loss: 1.5450, Val Accuracy: 0.4062
Epoch 1375/10000, Train Loss: 1.5417, Train Accuracy: 0.4185, Val Loss: 1.5448, Val Accuracy: 0.4062
Epoch 1376/10000, Train Loss: 1.5427, Train Accuracy: 0.3940, Val Loss: 1.5447, Val Accuracy: 0.4062
Epoch 1377/10000, Train Loss: 1.5427, Train Accuracy: 0.4107, Val Loss: 1.5445, Val Accuracy: 0.4062
Epoch 1378/10000, Train Loss: 1.5424, Train Accuracy: 0.4007, Val Loss: 1.5444, Val Accuracy: 0.4062
Epoch 1379/10000, Train Loss: 1.5438, Train Accuracy: 0.4029, Val Loss: 1.5443, Val Accuracy: 0.4062
Epoch 1380/10000, Train Loss: 1.5386, Train Accuracy: 0.4141, Val Loss: 1.5441, Val Accuracy: 0.4062
Epoch 1381/10000, Train Loss: 1.5430, Train Accuracy: 0.4029, Val Loss: 1.5440, Val Accuracy: 0.4018
Epoch 1382/10000, Train Loss: 1.5423, Train Accuracy: 0.4174, Val Loss: 1.5438, Val Accuracy: 0.4018
Epoch 1383/10000, Train Loss: 1.5388, Train Accuracy: 0.4241, Val Loss: 1.5437, Val Accuracy: 0.4018
Epoch 1384/10000, Train Loss: 1.5417, Train Accuracy: 0.4018, Val Loss: 1.5435, Val Accuracy: 0.4018
Epoch 1385/10000, Train Loss: 1.5405, Train Accuracy: 0.4062, Val Loss: 1.5434, Val Accuracy: 0.4018
Epoch 1386/10000, Train Loss: 1.5441, Train Accuracy: 0.3984, Val Loss: 1.5432, Val Accuracy: 0.4018
Epoch 1387/10000, Train Loss: 1.5417, Train Accuracy: 0.4018, Val Loss: 1.5431, Val Accuracy: 0.4018
Epoch 1388/10000, Train Loss: 1.5405, Train Accuracy: 0.4107, Val Loss: 1.5429, Val Accuracy: 0.4018
Epoch 1389/10000, Train Loss: 1.5417, Train Accuracy: 0.4074, Val Loss: 1.5428, Val Accuracy: 0.4018
Epoch 1390/10000, Train Loss: 1.5406, Train Accuracy: 0.4040, Val Loss: 1.5426, Val Accuracy: 0.4018
Epoch 1391/10000, Train Loss: 1.5386, Train Accuracy: 0.4085, Val Loss: 1.5424, Val Accuracy: 0.4018
Epoch 1392/10000, Train Loss: 1.5385, Train Accuracy: 0.4074, Val Loss: 1.5423, Val Accuracy: 0.4018
Epoch 1393/10000, Train Loss: 1.5399, Train Accuracy: 0.4085, Val Loss: 1.5421, Val Accuracy: 0.4018
Epoch 1394/10000, Train Loss: 1.5395, Train Accuracy: 0.4007, Val Loss: 1.5420, Val Accuracy: 0.3973
Epoch 1395/10000, Train Loss: 1.5392, Train Accuracy: 0.4007, Val Loss: 1.5419, Val Accuracy: 0.4062
Epoch 1396/10000, Train Loss: 1.5406, Train Accuracy: 0.3895, Val Loss: 1.5417, Val Accuracy: 0.4062
Epoch 1397/10000, Train Loss: 1.5428, Train Accuracy: 0.3929, Val Loss: 1.5415, Val Accuracy: 0.4062
Epoch 1398/10000, Train Loss: 1.5403, Train Accuracy: 0.3940, Val Loss: 1.5414, Val Accuracy: 0.4062
Epoch 1399/10000, Train Loss: 1.5382, Train Accuracy: 0.3984, Val Loss: 1.5412, Val Accuracy: 0.4062
Epoch 1400/10000, Train Loss: 1.5413, Train Accuracy: 0.3895, Val Loss: 1.5410, Val Accuracy: 0.4018
Epoch 1401/10000, Train Loss: 1.5372, Train Accuracy: 0.4018, Val Loss: 1.5409, Val Accuracy: 0.4018
Epoch 1402/10000, Train Loss: 1.5393, Train Accuracy: 0.4074, Val Loss: 1.5407, Val Accuracy: 0.4018
Epoch 1403/10000, Train Loss: 1.5390, Train Accuracy: 0.4029, Val Loss: 1.5406, Val Accuracy: 0.4018
Epoch 1404/10000, Train Loss: 1.5357, Train Accuracy: 0.4051, Val Loss: 1.5404, Val Accuracy: 0.4018
Epoch 1405/10000, Train Loss: 1.5400, Train Accuracy: 0.4118, Val Loss: 1.5403, Val Accuracy: 0.4018
Epoch 1406/10000, Train Loss: 1.5365, Train Accuracy: 0.4129, Val Loss: 1.5402, Val Accuracy: 0.4018
Epoch 1407/10000, Train Loss: 1.5368, Train Accuracy: 0.4029, Val Loss: 1.5400, Val Accuracy: 0.4018
Epoch 1408/10000, Train Loss: 1.5387, Train Accuracy: 0.3839, Val Loss: 1.5399, Val Accuracy: 0.4062
Epoch 1409/10000, Train Loss: 1.5378, Train Accuracy: 0.4118, Val Loss: 1.5398, Val Accuracy: 0.4062
Epoch 1410/10000, Train Loss: 1.5330, Train Accuracy: 0.4118, Val Loss: 1.5396, Val Accuracy: 0.4062
Epoch 1411/10000, Train Loss: 1.5374, Train Accuracy: 0.4163, Val Loss: 1.5394, Val Accuracy: 0.4062
Epoch 1412/10000, Train Loss: 1.5370, Train Accuracy: 0.4185, Val Loss: 1.5393, Val Accuracy: 0.4062
Epoch 1413/10000, Train Loss: 1.5400, Train Accuracy: 0.4062, Val Loss: 1.5391, Val Accuracy: 0.4062
Epoch 1414/10000, Train Loss: 1.5401, Train Accuracy: 0.4018, Val Loss: 1.5390, Val Accuracy: 0.4062
Epoch 1415/10000, Train Loss: 1.5353, Train Accuracy: 0.4118, Val Loss: 1.5388, Val Accuracy: 0.4062
Epoch 1416/10000, Train Loss: 1.5361, Train Accuracy: 0.4085, Val Loss: 1.5386, Val Accuracy: 0.4062
Epoch 1417/10000, Train Loss: 1.5336, Train Accuracy: 0.4018, Val Loss: 1.5385, Val Accuracy: 0.4062
Epoch 1418/10000, Train Loss: 1.5393, Train Accuracy: 0.3873, Val Loss: 1.5383, Val Accuracy: 0.4107
Epoch 1419/10000, Train Loss: 1.5368, Train Accuracy: 0.4051, Val Loss: 1.5382, Val Accuracy: 0.4107
Epoch 1420/10000, Train Loss: 1.5341, Train Accuracy: 0.4018, Val Loss: 1.5380, Val Accuracy: 0.4107
Epoch 1421/10000, Train Loss: 1.5383, Train Accuracy: 0.3951, Val Loss: 1.5379, Val Accuracy: 0.4107
Epoch 1422/10000, Train Loss: 1.5380, Train Accuracy: 0.4096, Val Loss: 1.5377, Val Accuracy: 0.4062
Epoch 1423/10000, Train Loss: 1.5375, Train Accuracy: 0.4129, Val Loss: 1.5375, Val Accuracy: 0.4062
Epoch 1424/10000, Train Loss: 1.5343, Train Accuracy: 0.3951, Val Loss: 1.5374, Val Accuracy: 0.4062
Epoch 1425/10000, Train Loss: 1.5371, Train Accuracy: 0.4330, Val Loss: 1.5372, Val Accuracy: 0.4062
Epoch 1426/10000, Train Loss: 1.5354, Train Accuracy: 0.3895, Val Loss: 1.5371, Val Accuracy: 0.4062
Epoch 1427/10000, Train Loss: 1.5388, Train Accuracy: 0.3962, Val Loss: 1.5369, Val Accuracy: 0.4062
Epoch 1428/10000, Train Loss: 1.5372, Train Accuracy: 0.4129, Val Loss: 1.5368, Val Accuracy: 0.4062
Epoch 1429/10000, Train Loss: 1.5313, Train Accuracy: 0.4208, Val Loss: 1.5366, Val Accuracy: 0.4062
Epoch 1430/10000, Train Loss: 1.5352, Train Accuracy: 0.4241, Val Loss: 1.5365, Val Accuracy: 0.4062
Epoch 1431/10000, Train Loss: 1.5361, Train Accuracy: 0.4040, Val Loss: 1.5363, Val Accuracy: 0.4062
Epoch 1432/10000, Train Loss: 1.5346, Train Accuracy: 0.4252, Val Loss: 1.5361, Val Accuracy: 0.4062
Epoch 1433/10000, Train Loss: 1.5338, Train Accuracy: 0.4230, Val Loss: 1.5360, Val Accuracy: 0.4062
Epoch 1434/10000, Train Loss: 1.5357, Train Accuracy: 0.4029, Val Loss: 1.5358, Val Accuracy: 0.4062
Epoch 1435/10000, Train Loss: 1.5340, Train Accuracy: 0.3984, Val Loss: 1.5357, Val Accuracy: 0.4062
Epoch 1436/10000, Train Loss: 1.5350, Train Accuracy: 0.4129, Val Loss: 1.5356, Val Accuracy: 0.4062
Epoch 1437/10000, Train Loss: 1.5354, Train Accuracy: 0.3940, Val Loss: 1.5354, Val Accuracy: 0.4062
Epoch 1438/10000, Train Loss: 1.5337, Train Accuracy: 0.4107, Val Loss: 1.5353, Val Accuracy: 0.4062
Epoch 1439/10000, Train Loss: 1.5327, Train Accuracy: 0.4018, Val Loss: 1.5352, Val Accuracy: 0.4062
Epoch 1440/10000, Train Loss: 1.5346, Train Accuracy: 0.4018, Val Loss: 1.5350, Val Accuracy: 0.4062
Epoch 1441/10000, Train Loss: 1.5341, Train Accuracy: 0.4141, Val Loss: 1.5349, Val Accuracy: 0.4062
Epoch 1442/10000, Train Loss: 1.5298, Train Accuracy: 0.4163, Val Loss: 1.5347, Val Accuracy: 0.4062
Epoch 1443/10000, Train Loss: 1.5295, Train Accuracy: 0.4062, Val Loss: 1.5345, Val Accuracy: 0.4062
Epoch 1444/10000, Train Loss: 1.5324, Train Accuracy: 0.4219, Val Loss: 1.5344, Val Accuracy: 0.4062
Epoch 1445/10000, Train Loss: 1.5313, Train Accuracy: 0.4230, Val Loss: 1.5343, Val Accuracy: 0.4062
Epoch 1446/10000, Train Loss: 1.5331, Train Accuracy: 0.4029, Val Loss: 1.5341, Val Accuracy: 0.4062
Epoch 1447/10000, Train Loss: 1.5330, Train Accuracy: 0.4141, Val Loss: 1.5339, Val Accuracy: 0.4062
Epoch 1448/10000, Train Loss: 1.5337, Train Accuracy: 0.4141, Val Loss: 1.5337, Val Accuracy: 0.4062
Epoch 1449/10000, Train Loss: 1.5297, Train Accuracy: 0.4029, Val Loss: 1.5335, Val Accuracy: 0.4062
Epoch 1450/10000, Train Loss: 1.5293, Train Accuracy: 0.4319, Val Loss: 1.5334, Val Accuracy: 0.4062
Epoch 1451/10000, Train Loss: 1.5295, Train Accuracy: 0.4051, Val Loss: 1.5332, Val Accuracy: 0.4062
Epoch 1452/10000, Train Loss: 1.5308, Train Accuracy: 0.4163, Val Loss: 1.5330, Val Accuracy: 0.4107
Epoch 1453/10000, Train Loss: 1.5278, Train Accuracy: 0.4286, Val Loss: 1.5329, Val Accuracy: 0.4107
Epoch 1454/10000, Train Loss: 1.5259, Train Accuracy: 0.4118, Val Loss: 1.5327, Val Accuracy: 0.4107
Epoch 1455/10000, Train Loss: 1.5296, Train Accuracy: 0.4208, Val Loss: 1.5326, Val Accuracy: 0.4107
Epoch 1456/10000, Train Loss: 1.5308, Train Accuracy: 0.4241, Val Loss: 1.5324, Val Accuracy: 0.4152
Epoch 1457/10000, Train Loss: 1.5300, Train Accuracy: 0.4185, Val Loss: 1.5322, Val Accuracy: 0.4152
Epoch 1458/10000, Train Loss: 1.5303, Train Accuracy: 0.4118, Val Loss: 1.5321, Val Accuracy: 0.4196
Epoch 1459/10000, Train Loss: 1.5270, Train Accuracy: 0.4353, Val Loss: 1.5319, Val Accuracy: 0.4152
Epoch 1460/10000, Train Loss: 1.5315, Train Accuracy: 0.4208, Val Loss: 1.5318, Val Accuracy: 0.4196
Epoch 1461/10000, Train Loss: 1.5307, Train Accuracy: 0.4152, Val Loss: 1.5316, Val Accuracy: 0.4196
Epoch 1462/10000, Train Loss: 1.5274, Train Accuracy: 0.4185, Val Loss: 1.5314, Val Accuracy: 0.4196
Epoch 1463/10000, Train Loss: 1.5279, Train Accuracy: 0.4219, Val Loss: 1.5313, Val Accuracy: 0.4241
Epoch 1464/10000, Train Loss: 1.5272, Train Accuracy: 0.4040, Val Loss: 1.5311, Val Accuracy: 0.4241
Epoch 1465/10000, Train Loss: 1.5335, Train Accuracy: 0.4007, Val Loss: 1.5309, Val Accuracy: 0.4241
Epoch 1466/10000, Train Loss: 1.5297, Train Accuracy: 0.4275, Val Loss: 1.5308, Val Accuracy: 0.4241
Epoch 1467/10000, Train Loss: 1.5292, Train Accuracy: 0.4007, Val Loss: 1.5306, Val Accuracy: 0.4241
Epoch 1468/10000, Train Loss: 1.5274, Train Accuracy: 0.4275, Val Loss: 1.5304, Val Accuracy: 0.4241
Epoch 1469/10000, Train Loss: 1.5257, Train Accuracy: 0.4074, Val Loss: 1.5303, Val Accuracy: 0.4241
Epoch 1470/10000, Train Loss: 1.5302, Train Accuracy: 0.4107, Val Loss: 1.5302, Val Accuracy: 0.4241
Epoch 1471/10000, Train Loss: 1.5287, Train Accuracy: 0.4107, Val Loss: 1.5301, Val Accuracy: 0.4241
Epoch 1472/10000, Train Loss: 1.5284, Train Accuracy: 0.4219, Val Loss: 1.5299, Val Accuracy: 0.4241
Epoch 1473/10000, Train Loss: 1.5320, Train Accuracy: 0.3951, Val Loss: 1.5298, Val Accuracy: 0.4241
Epoch 1474/10000, Train Loss: 1.5279, Train Accuracy: 0.4163, Val Loss: 1.5296, Val Accuracy: 0.4241
Epoch 1475/10000, Train Loss: 1.5282, Train Accuracy: 0.4185, Val Loss: 1.5294, Val Accuracy: 0.4241
Epoch 1476/10000, Train Loss: 1.5272, Train Accuracy: 0.4163, Val Loss: 1.5293, Val Accuracy: 0.4241
Epoch 1477/10000, Train Loss: 1.5266, Train Accuracy: 0.4275, Val Loss: 1.5292, Val Accuracy: 0.4241
Epoch 1478/10000, Train Loss: 1.5251, Train Accuracy: 0.4118, Val Loss: 1.5290, Val Accuracy: 0.4241
Epoch 1479/10000, Train Loss: 1.5272, Train Accuracy: 0.4051, Val Loss: 1.5288, Val Accuracy: 0.4241
Epoch 1480/10000, Train Loss: 1.5278, Train Accuracy: 0.4085, Val Loss: 1.5286, Val Accuracy: 0.4241
Epoch 1481/10000, Train Loss: 1.5272, Train Accuracy: 0.4029, Val Loss: 1.5285, Val Accuracy: 0.4241
Epoch 1482/10000, Train Loss: 1.5235, Train Accuracy: 0.4196, Val Loss: 1.5283, Val Accuracy: 0.4286
Epoch 1483/10000, Train Loss: 1.5247, Train Accuracy: 0.4051, Val Loss: 1.5281, Val Accuracy: 0.4241
Epoch 1484/10000, Train Loss: 1.5247, Train Accuracy: 0.4163, Val Loss: 1.5280, Val Accuracy: 0.4286
Epoch 1485/10000, Train Loss: 1.5255, Train Accuracy: 0.3951, Val Loss: 1.5278, Val Accuracy: 0.4286
Epoch 1486/10000, Train Loss: 1.5225, Train Accuracy: 0.4018, Val Loss: 1.5276, Val Accuracy: 0.4286
Epoch 1487/10000, Train Loss: 1.5235, Train Accuracy: 0.4263, Val Loss: 1.5275, Val Accuracy: 0.4286
Epoch 1488/10000, Train Loss: 1.5204, Train Accuracy: 0.4319, Val Loss: 1.5273, Val Accuracy: 0.4286
Epoch 1489/10000, Train Loss: 1.5253, Train Accuracy: 0.4085, Val Loss: 1.5272, Val Accuracy: 0.4286
Epoch 1490/10000, Train Loss: 1.5271, Train Accuracy: 0.3984, Val Loss: 1.5270, Val Accuracy: 0.4286
Epoch 1491/10000, Train Loss: 1.5228, Train Accuracy: 0.4152, Val Loss: 1.5269, Val Accuracy: 0.4286
Epoch 1492/10000, Train Loss: 1.5273, Train Accuracy: 0.4085, Val Loss: 1.5267, Val Accuracy: 0.4286
Epoch 1493/10000, Train Loss: 1.5277, Train Accuracy: 0.4029, Val Loss: 1.5266, Val Accuracy: 0.4286
Epoch 1494/10000, Train Loss: 1.5227, Train Accuracy: 0.4185, Val Loss: 1.5264, Val Accuracy: 0.4286
Epoch 1495/10000, Train Loss: 1.5263, Train Accuracy: 0.4196, Val Loss: 1.5262, Val Accuracy: 0.4330
Epoch 1496/10000, Train Loss: 1.5247, Train Accuracy: 0.4275, Val Loss: 1.5260, Val Accuracy: 0.4330
Epoch 1497/10000, Train Loss: 1.5252, Train Accuracy: 0.4107, Val Loss: 1.5259, Val Accuracy: 0.4330
Epoch 1498/10000, Train Loss: 1.5246, Train Accuracy: 0.4319, Val Loss: 1.5258, Val Accuracy: 0.4330
Epoch 1499/10000, Train Loss: 1.5239, Train Accuracy: 0.4129, Val Loss: 1.5256, Val Accuracy: 0.4330
Epoch 1500/10000, Train Loss: 1.5193, Train Accuracy: 0.4241, Val Loss: 1.5254, Val Accuracy: 0.4330
Epoch 1501/10000, Train Loss: 1.5223, Train Accuracy: 0.4118, Val Loss: 1.5252, Val Accuracy: 0.4330
Epoch 1502/10000, Train Loss: 1.5247, Train Accuracy: 0.4219, Val Loss: 1.5250, Val Accuracy: 0.4330
Epoch 1503/10000, Train Loss: 1.5222, Train Accuracy: 0.4051, Val Loss: 1.5249, Val Accuracy: 0.4330
Epoch 1504/10000, Train Loss: 1.5239, Train Accuracy: 0.3973, Val Loss: 1.5247, Val Accuracy: 0.4330
Epoch 1505/10000, Train Loss: 1.5204, Train Accuracy: 0.4342, Val Loss: 1.5245, Val Accuracy: 0.4330
Epoch 1506/10000, Train Loss: 1.5182, Train Accuracy: 0.4364, Val Loss: 1.5244, Val Accuracy: 0.4330
Epoch 1507/10000, Train Loss: 1.5229, Train Accuracy: 0.4107, Val Loss: 1.5242, Val Accuracy: 0.4330
Epoch 1508/10000, Train Loss: 1.5216, Train Accuracy: 0.4208, Val Loss: 1.5241, Val Accuracy: 0.4330
Epoch 1509/10000, Train Loss: 1.5222, Train Accuracy: 0.4208, Val Loss: 1.5239, Val Accuracy: 0.4330
Epoch 1510/10000, Train Loss: 1.5232, Train Accuracy: 0.4096, Val Loss: 1.5238, Val Accuracy: 0.4330
Epoch 1511/10000, Train Loss: 1.5249, Train Accuracy: 0.4040, Val Loss: 1.5235, Val Accuracy: 0.4330
Epoch 1512/10000, Train Loss: 1.5184, Train Accuracy: 0.4040, Val Loss: 1.5234, Val Accuracy: 0.4330
Epoch 1513/10000, Train Loss: 1.5214, Train Accuracy: 0.4297, Val Loss: 1.5232, Val Accuracy: 0.4330
Epoch 1514/10000, Train Loss: 1.5223, Train Accuracy: 0.4141, Val Loss: 1.5230, Val Accuracy: 0.4330
Epoch 1515/10000, Train Loss: 1.5216, Train Accuracy: 0.4219, Val Loss: 1.5229, Val Accuracy: 0.4330
Epoch 1516/10000, Train Loss: 1.5214, Train Accuracy: 0.4118, Val Loss: 1.5228, Val Accuracy: 0.4330
Epoch 1517/10000, Train Loss: 1.5166, Train Accuracy: 0.4263, Val Loss: 1.5227, Val Accuracy: 0.4330
Epoch 1518/10000, Train Loss: 1.5202, Train Accuracy: 0.4096, Val Loss: 1.5225, Val Accuracy: 0.4330
Epoch 1519/10000, Train Loss: 1.5191, Train Accuracy: 0.3984, Val Loss: 1.5224, Val Accuracy: 0.4330
Epoch 1520/10000, Train Loss: 1.5219, Train Accuracy: 0.4174, Val Loss: 1.5222, Val Accuracy: 0.4330
Epoch 1521/10000, Train Loss: 1.5236, Train Accuracy: 0.4330, Val Loss: 1.5220, Val Accuracy: 0.4330
Epoch 1522/10000, Train Loss: 1.5202, Train Accuracy: 0.4297, Val Loss: 1.5219, Val Accuracy: 0.4330
Epoch 1523/10000, Train Loss: 1.5223, Train Accuracy: 0.4174, Val Loss: 1.5217, Val Accuracy: 0.4330
Epoch 1524/10000, Train Loss: 1.5213, Train Accuracy: 0.4141, Val Loss: 1.5215, Val Accuracy: 0.4330
Epoch 1525/10000, Train Loss: 1.5179, Train Accuracy: 0.4085, Val Loss: 1.5214, Val Accuracy: 0.4330
Epoch 1526/10000, Train Loss: 1.5184, Train Accuracy: 0.4353, Val Loss: 1.5212, Val Accuracy: 0.4330
Epoch 1527/10000, Train Loss: 1.5199, Train Accuracy: 0.4263, Val Loss: 1.5210, Val Accuracy: 0.4330
Epoch 1528/10000, Train Loss: 1.5177, Train Accuracy: 0.4219, Val Loss: 1.5209, Val Accuracy: 0.4330
Epoch 1529/10000, Train Loss: 1.5222, Train Accuracy: 0.4096, Val Loss: 1.5207, Val Accuracy: 0.4330
Epoch 1530/10000, Train Loss: 1.5183, Train Accuracy: 0.4196, Val Loss: 1.5205, Val Accuracy: 0.4330
Epoch 1531/10000, Train Loss: 1.5167, Train Accuracy: 0.4386, Val Loss: 1.5204, Val Accuracy: 0.4330
Epoch 1532/10000, Train Loss: 1.5160, Train Accuracy: 0.4129, Val Loss: 1.5202, Val Accuracy: 0.4330
Epoch 1533/10000, Train Loss: 1.5196, Train Accuracy: 0.4074, Val Loss: 1.5201, Val Accuracy: 0.4330
Epoch 1534/10000, Train Loss: 1.5151, Train Accuracy: 0.4118, Val Loss: 1.5199, Val Accuracy: 0.4330
Epoch 1535/10000, Train Loss: 1.5155, Train Accuracy: 0.4219, Val Loss: 1.5197, Val Accuracy: 0.4375
Epoch 1536/10000, Train Loss: 1.5146, Train Accuracy: 0.4141, Val Loss: 1.5195, Val Accuracy: 0.4375
Epoch 1537/10000, Train Loss: 1.5197, Train Accuracy: 0.4397, Val Loss: 1.5194, Val Accuracy: 0.4375
Epoch 1538/10000, Train Loss: 1.5196, Train Accuracy: 0.4141, Val Loss: 1.5192, Val Accuracy: 0.4375
Epoch 1539/10000, Train Loss: 1.5132, Train Accuracy: 0.4286, Val Loss: 1.5191, Val Accuracy: 0.4375
Epoch 1540/10000, Train Loss: 1.5193, Train Accuracy: 0.4208, Val Loss: 1.5189, Val Accuracy: 0.4375
Epoch 1541/10000, Train Loss: 1.5154, Train Accuracy: 0.4152, Val Loss: 1.5187, Val Accuracy: 0.4375
Epoch 1542/10000, Train Loss: 1.5160, Train Accuracy: 0.4174, Val Loss: 1.5186, Val Accuracy: 0.4375
Epoch 1543/10000, Train Loss: 1.5175, Train Accuracy: 0.4241, Val Loss: 1.5184, Val Accuracy: 0.4375
Epoch 1544/10000, Train Loss: 1.5126, Train Accuracy: 0.4464, Val Loss: 1.5183, Val Accuracy: 0.4375
Epoch 1545/10000, Train Loss: 1.5128, Train Accuracy: 0.4330, Val Loss: 1.5181, Val Accuracy: 0.4375
Epoch 1546/10000, Train Loss: 1.5155, Train Accuracy: 0.4051, Val Loss: 1.5179, Val Accuracy: 0.4375
Epoch 1547/10000, Train Loss: 1.5147, Train Accuracy: 0.4230, Val Loss: 1.5178, Val Accuracy: 0.4330
Epoch 1548/10000, Train Loss: 1.5149, Train Accuracy: 0.4152, Val Loss: 1.5176, Val Accuracy: 0.4330
Epoch 1549/10000, Train Loss: 1.5152, Train Accuracy: 0.4163, Val Loss: 1.5174, Val Accuracy: 0.4286
Epoch 1550/10000, Train Loss: 1.5169, Train Accuracy: 0.4230, Val Loss: 1.5173, Val Accuracy: 0.4286
Epoch 1551/10000, Train Loss: 1.5170, Train Accuracy: 0.4196, Val Loss: 1.5171, Val Accuracy: 0.4286
Epoch 1552/10000, Train Loss: 1.5164, Train Accuracy: 0.4185, Val Loss: 1.5170, Val Accuracy: 0.4286
Epoch 1553/10000, Train Loss: 1.5137, Train Accuracy: 0.4208, Val Loss: 1.5168, Val Accuracy: 0.4286
Epoch 1554/10000, Train Loss: 1.5116, Train Accuracy: 0.4263, Val Loss: 1.5167, Val Accuracy: 0.4286
Epoch 1555/10000, Train Loss: 1.5178, Train Accuracy: 0.4118, Val Loss: 1.5165, Val Accuracy: 0.4286
Epoch 1556/10000, Train Loss: 1.5180, Train Accuracy: 0.4152, Val Loss: 1.5163, Val Accuracy: 0.4286
Epoch 1557/10000, Train Loss: 1.5098, Train Accuracy: 0.4475, Val Loss: 1.5162, Val Accuracy: 0.4241
Epoch 1558/10000, Train Loss: 1.5172, Train Accuracy: 0.4208, Val Loss: 1.5160, Val Accuracy: 0.4241
Epoch 1559/10000, Train Loss: 1.5178, Train Accuracy: 0.4219, Val Loss: 1.5158, Val Accuracy: 0.4241
Epoch 1560/10000, Train Loss: 1.5076, Train Accuracy: 0.4375, Val Loss: 1.5157, Val Accuracy: 0.4286
Epoch 1561/10000, Train Loss: 1.5112, Train Accuracy: 0.4241, Val Loss: 1.5155, Val Accuracy: 0.4330
Epoch 1562/10000, Train Loss: 1.5158, Train Accuracy: 0.4185, Val Loss: 1.5154, Val Accuracy: 0.4286
Epoch 1563/10000, Train Loss: 1.5120, Train Accuracy: 0.4297, Val Loss: 1.5152, Val Accuracy: 0.4286
Epoch 1564/10000, Train Loss: 1.5138, Train Accuracy: 0.4018, Val Loss: 1.5150, Val Accuracy: 0.4330
Epoch 1565/10000, Train Loss: 1.5099, Train Accuracy: 0.4386, Val Loss: 1.5149, Val Accuracy: 0.4330
Epoch 1566/10000, Train Loss: 1.5123, Train Accuracy: 0.4185, Val Loss: 1.5147, Val Accuracy: 0.4286
Epoch 1567/10000, Train Loss: 1.5144, Train Accuracy: 0.4062, Val Loss: 1.5146, Val Accuracy: 0.4286
Epoch 1568/10000, Train Loss: 1.5126, Train Accuracy: 0.4464, Val Loss: 1.5144, Val Accuracy: 0.4286
Epoch 1569/10000, Train Loss: 1.5177, Train Accuracy: 0.4219, Val Loss: 1.5142, Val Accuracy: 0.4286
Epoch 1570/10000, Train Loss: 1.5115, Train Accuracy: 0.4118, Val Loss: 1.5140, Val Accuracy: 0.4286
Epoch 1571/10000, Train Loss: 1.5111, Train Accuracy: 0.4330, Val Loss: 1.5138, Val Accuracy: 0.4286
Epoch 1572/10000, Train Loss: 1.5138, Train Accuracy: 0.4230, Val Loss: 1.5137, Val Accuracy: 0.4286
Epoch 1573/10000, Train Loss: 1.5159, Train Accuracy: 0.4018, Val Loss: 1.5135, Val Accuracy: 0.4286
Epoch 1574/10000, Train Loss: 1.5110, Train Accuracy: 0.4230, Val Loss: 1.5134, Val Accuracy: 0.4286
Epoch 1575/10000, Train Loss: 1.5096, Train Accuracy: 0.4297, Val Loss: 1.5132, Val Accuracy: 0.4286
Epoch 1576/10000, Train Loss: 1.5104, Train Accuracy: 0.4129, Val Loss: 1.5131, Val Accuracy: 0.4286
Epoch 1577/10000, Train Loss: 1.5078, Train Accuracy: 0.4174, Val Loss: 1.5129, Val Accuracy: 0.4286
Epoch 1578/10000, Train Loss: 1.5142, Train Accuracy: 0.4141, Val Loss: 1.5128, Val Accuracy: 0.4286
Epoch 1579/10000, Train Loss: 1.5132, Train Accuracy: 0.4062, Val Loss: 1.5127, Val Accuracy: 0.4286
Epoch 1580/10000, Train Loss: 1.5083, Train Accuracy: 0.4364, Val Loss: 1.5125, Val Accuracy: 0.4286
Epoch 1581/10000, Train Loss: 1.5057, Train Accuracy: 0.4431, Val Loss: 1.5124, Val Accuracy: 0.4286
Epoch 1582/10000, Train Loss: 1.5128, Train Accuracy: 0.4275, Val Loss: 1.5123, Val Accuracy: 0.4286
Epoch 1583/10000, Train Loss: 1.5104, Train Accuracy: 0.4152, Val Loss: 1.5121, Val Accuracy: 0.4286
Epoch 1584/10000, Train Loss: 1.5061, Train Accuracy: 0.4420, Val Loss: 1.5119, Val Accuracy: 0.4286
Epoch 1585/10000, Train Loss: 1.5109, Train Accuracy: 0.4196, Val Loss: 1.5117, Val Accuracy: 0.4286
Epoch 1586/10000, Train Loss: 1.5081, Train Accuracy: 0.4330, Val Loss: 1.5115, Val Accuracy: 0.4286
Epoch 1587/10000, Train Loss: 1.5089, Train Accuracy: 0.4330, Val Loss: 1.5113, Val Accuracy: 0.4286
Epoch 1588/10000, Train Loss: 1.5144, Train Accuracy: 0.4219, Val Loss: 1.5111, Val Accuracy: 0.4286
Epoch 1589/10000, Train Loss: 1.5077, Train Accuracy: 0.4219, Val Loss: 1.5110, Val Accuracy: 0.4286
Epoch 1590/10000, Train Loss: 1.5084, Train Accuracy: 0.4208, Val Loss: 1.5109, Val Accuracy: 0.4286
Epoch 1591/10000, Train Loss: 1.5062, Train Accuracy: 0.4408, Val Loss: 1.5107, Val Accuracy: 0.4286
Epoch 1592/10000, Train Loss: 1.5084, Train Accuracy: 0.4252, Val Loss: 1.5106, Val Accuracy: 0.4286
Epoch 1593/10000, Train Loss: 1.5099, Train Accuracy: 0.4286, Val Loss: 1.5104, Val Accuracy: 0.4286
Epoch 1594/10000, Train Loss: 1.5087, Train Accuracy: 0.4275, Val Loss: 1.5102, Val Accuracy: 0.4286
Epoch 1595/10000, Train Loss: 1.5046, Train Accuracy: 0.4364, Val Loss: 1.5100, Val Accuracy: 0.4330
Epoch 1596/10000, Train Loss: 1.5087, Train Accuracy: 0.4275, Val Loss: 1.5099, Val Accuracy: 0.4330
Epoch 1597/10000, Train Loss: 1.5092, Train Accuracy: 0.4107, Val Loss: 1.5097, Val Accuracy: 0.4375
Epoch 1598/10000, Train Loss: 1.5100, Train Accuracy: 0.4330, Val Loss: 1.5095, Val Accuracy: 0.4375
Epoch 1599/10000, Train Loss: 1.5046, Train Accuracy: 0.4319, Val Loss: 1.5094, Val Accuracy: 0.4375
Epoch 1600/10000, Train Loss: 1.5037, Train Accuracy: 0.4330, Val Loss: 1.5092, Val Accuracy: 0.4330
Epoch 1601/10000, Train Loss: 1.5084, Train Accuracy: 0.4263, Val Loss: 1.5090, Val Accuracy: 0.4330
Epoch 1602/10000, Train Loss: 1.5017, Train Accuracy: 0.4420, Val Loss: 1.5089, Val Accuracy: 0.4330
Epoch 1603/10000, Train Loss: 1.5071, Train Accuracy: 0.4029, Val Loss: 1.5087, Val Accuracy: 0.4330
Epoch 1604/10000, Train Loss: 1.5114, Train Accuracy: 0.4163, Val Loss: 1.5086, Val Accuracy: 0.4375
Epoch 1605/10000, Train Loss: 1.5073, Train Accuracy: 0.4107, Val Loss: 1.5084, Val Accuracy: 0.4375
Epoch 1606/10000, Train Loss: 1.5012, Train Accuracy: 0.4275, Val Loss: 1.5083, Val Accuracy: 0.4330
Epoch 1607/10000, Train Loss: 1.5051, Train Accuracy: 0.4275, Val Loss: 1.5081, Val Accuracy: 0.4330
Epoch 1608/10000, Train Loss: 1.5089, Train Accuracy: 0.4386, Val Loss: 1.5079, Val Accuracy: 0.4330
Epoch 1609/10000, Train Loss: 1.5088, Train Accuracy: 0.4096, Val Loss: 1.5077, Val Accuracy: 0.4330
Epoch 1610/10000, Train Loss: 1.5024, Train Accuracy: 0.4286, Val Loss: 1.5076, Val Accuracy: 0.4330
Epoch 1611/10000, Train Loss: 1.5030, Train Accuracy: 0.4464, Val Loss: 1.5075, Val Accuracy: 0.4330
Epoch 1612/10000, Train Loss: 1.5071, Train Accuracy: 0.4342, Val Loss: 1.5073, Val Accuracy: 0.4375
Epoch 1613/10000, Train Loss: 1.5067, Train Accuracy: 0.4420, Val Loss: 1.5072, Val Accuracy: 0.4420
Epoch 1614/10000, Train Loss: 1.5048, Train Accuracy: 0.4364, Val Loss: 1.5070, Val Accuracy: 0.4420
Epoch 1615/10000, Train Loss: 1.5014, Train Accuracy: 0.4286, Val Loss: 1.5068, Val Accuracy: 0.4420
Epoch 1616/10000, Train Loss: 1.5040, Train Accuracy: 0.4196, Val Loss: 1.5066, Val Accuracy: 0.4464
Epoch 1617/10000, Train Loss: 1.5048, Train Accuracy: 0.4297, Val Loss: 1.5065, Val Accuracy: 0.4464
Epoch 1618/10000, Train Loss: 1.5064, Train Accuracy: 0.4375, Val Loss: 1.5063, Val Accuracy: 0.4464
Epoch 1619/10000, Train Loss: 1.5031, Train Accuracy: 0.4342, Val Loss: 1.5061, Val Accuracy: 0.4509
Epoch 1620/10000, Train Loss: 1.5023, Train Accuracy: 0.4397, Val Loss: 1.5060, Val Accuracy: 0.4509
Epoch 1621/10000, Train Loss: 1.5019, Train Accuracy: 0.4408, Val Loss: 1.5058, Val Accuracy: 0.4509
Epoch 1622/10000, Train Loss: 1.5004, Train Accuracy: 0.4509, Val Loss: 1.5056, Val Accuracy: 0.4509
Epoch 1623/10000, Train Loss: 1.5028, Train Accuracy: 0.4196, Val Loss: 1.5055, Val Accuracy: 0.4509
Epoch 1624/10000, Train Loss: 1.5037, Train Accuracy: 0.4408, Val Loss: 1.5053, Val Accuracy: 0.4509
Epoch 1625/10000, Train Loss: 1.5056, Train Accuracy: 0.4163, Val Loss: 1.5052, Val Accuracy: 0.4509
Epoch 1626/10000, Train Loss: 1.5014, Train Accuracy: 0.4386, Val Loss: 1.5050, Val Accuracy: 0.4509
Epoch 1627/10000, Train Loss: 1.5087, Train Accuracy: 0.4219, Val Loss: 1.5048, Val Accuracy: 0.4509
Epoch 1628/10000, Train Loss: 1.5035, Train Accuracy: 0.4319, Val Loss: 1.5047, Val Accuracy: 0.4509
Epoch 1629/10000, Train Loss: 1.5044, Train Accuracy: 0.4085, Val Loss: 1.5046, Val Accuracy: 0.4509
Epoch 1630/10000, Train Loss: 1.4992, Train Accuracy: 0.4420, Val Loss: 1.5044, Val Accuracy: 0.4509
Epoch 1631/10000, Train Loss: 1.5036, Train Accuracy: 0.4062, Val Loss: 1.5042, Val Accuracy: 0.4509
Epoch 1632/10000, Train Loss: 1.5034, Train Accuracy: 0.4386, Val Loss: 1.5041, Val Accuracy: 0.4509
Epoch 1633/10000, Train Loss: 1.5086, Train Accuracy: 0.4230, Val Loss: 1.5039, Val Accuracy: 0.4509
Epoch 1634/10000, Train Loss: 1.4967, Train Accuracy: 0.4397, Val Loss: 1.5038, Val Accuracy: 0.4509
Epoch 1635/10000, Train Loss: 1.5059, Train Accuracy: 0.4196, Val Loss: 1.5036, Val Accuracy: 0.4509
Epoch 1636/10000, Train Loss: 1.5021, Train Accuracy: 0.4241, Val Loss: 1.5034, Val Accuracy: 0.4509
Epoch 1637/10000, Train Loss: 1.5029, Train Accuracy: 0.4286, Val Loss: 1.5033, Val Accuracy: 0.4509
Epoch 1638/10000, Train Loss: 1.5006, Train Accuracy: 0.4163, Val Loss: 1.5031, Val Accuracy: 0.4509
Epoch 1639/10000, Train Loss: 1.5005, Train Accuracy: 0.4152, Val Loss: 1.5029, Val Accuracy: 0.4509
Epoch 1640/10000, Train Loss: 1.5031, Train Accuracy: 0.4297, Val Loss: 1.5027, Val Accuracy: 0.4509
Epoch 1641/10000, Train Loss: 1.4989, Train Accuracy: 0.4141, Val Loss: 1.5025, Val Accuracy: 0.4509
Epoch 1642/10000, Train Loss: 1.5005, Train Accuracy: 0.4252, Val Loss: 1.5024, Val Accuracy: 0.4509
Epoch 1643/10000, Train Loss: 1.5007, Train Accuracy: 0.4464, Val Loss: 1.5023, Val Accuracy: 0.4509
Epoch 1644/10000, Train Loss: 1.5052, Train Accuracy: 0.4196, Val Loss: 1.5022, Val Accuracy: 0.4509
Epoch 1645/10000, Train Loss: 1.4995, Train Accuracy: 0.4375, Val Loss: 1.5020, Val Accuracy: 0.4509
Epoch 1646/10000, Train Loss: 1.4979, Train Accuracy: 0.4397, Val Loss: 1.5018, Val Accuracy: 0.4509
Epoch 1647/10000, Train Loss: 1.5019, Train Accuracy: 0.4219, Val Loss: 1.5017, Val Accuracy: 0.4509
Epoch 1648/10000, Train Loss: 1.5015, Train Accuracy: 0.4196, Val Loss: 1.5016, Val Accuracy: 0.4509
Epoch 1649/10000, Train Loss: 1.4988, Train Accuracy: 0.4397, Val Loss: 1.5014, Val Accuracy: 0.4509
Epoch 1650/10000, Train Loss: 1.4989, Train Accuracy: 0.4531, Val Loss: 1.5011, Val Accuracy: 0.4509
Epoch 1651/10000, Train Loss: 1.4964, Train Accuracy: 0.4230, Val Loss: 1.5010, Val Accuracy: 0.4509
Epoch 1652/10000, Train Loss: 1.5004, Train Accuracy: 0.4096, Val Loss: 1.5008, Val Accuracy: 0.4509
Epoch 1653/10000, Train Loss: 1.4967, Train Accuracy: 0.4342, Val Loss: 1.5007, Val Accuracy: 0.4509
Epoch 1654/10000, Train Loss: 1.4964, Train Accuracy: 0.4475, Val Loss: 1.5005, Val Accuracy: 0.4509
Epoch 1655/10000, Train Loss: 1.4968, Train Accuracy: 0.4375, Val Loss: 1.5004, Val Accuracy: 0.4509
Epoch 1656/10000, Train Loss: 1.4998, Train Accuracy: 0.4297, Val Loss: 1.5002, Val Accuracy: 0.4509
Epoch 1657/10000, Train Loss: 1.4966, Train Accuracy: 0.4475, Val Loss: 1.5000, Val Accuracy: 0.4509
Epoch 1658/10000, Train Loss: 1.4963, Train Accuracy: 0.4263, Val Loss: 1.4998, Val Accuracy: 0.4509
Epoch 1659/10000, Train Loss: 1.4985, Train Accuracy: 0.4185, Val Loss: 1.4997, Val Accuracy: 0.4464
Epoch 1660/10000, Train Loss: 1.4990, Train Accuracy: 0.4353, Val Loss: 1.4995, Val Accuracy: 0.4464
Epoch 1661/10000, Train Loss: 1.4972, Train Accuracy: 0.4286, Val Loss: 1.4994, Val Accuracy: 0.4509
Epoch 1662/10000, Train Loss: 1.4939, Train Accuracy: 0.4442, Val Loss: 1.4992, Val Accuracy: 0.4509
Epoch 1663/10000, Train Loss: 1.4956, Train Accuracy: 0.4342, Val Loss: 1.4990, Val Accuracy: 0.4464
Epoch 1664/10000, Train Loss: 1.4955, Train Accuracy: 0.4487, Val Loss: 1.4988, Val Accuracy: 0.4464
Epoch 1665/10000, Train Loss: 1.4977, Train Accuracy: 0.4353, Val Loss: 1.4986, Val Accuracy: 0.4464
Epoch 1666/10000, Train Loss: 1.4963, Train Accuracy: 0.4420, Val Loss: 1.4984, Val Accuracy: 0.4509
Epoch 1667/10000, Train Loss: 1.4944, Train Accuracy: 0.4275, Val Loss: 1.4983, Val Accuracy: 0.4509
Epoch 1668/10000, Train Loss: 1.4951, Train Accuracy: 0.4408, Val Loss: 1.4982, Val Accuracy: 0.4464
Epoch 1669/10000, Train Loss: 1.4973, Train Accuracy: 0.4375, Val Loss: 1.4981, Val Accuracy: 0.4464
Epoch 1670/10000, Train Loss: 1.4960, Train Accuracy: 0.4353, Val Loss: 1.4980, Val Accuracy: 0.4464
Epoch 1671/10000, Train Loss: 1.4970, Train Accuracy: 0.4420, Val Loss: 1.4978, Val Accuracy: 0.4464
Epoch 1672/10000, Train Loss: 1.4976, Train Accuracy: 0.4342, Val Loss: 1.4976, Val Accuracy: 0.4464
Epoch 1673/10000, Train Loss: 1.4931, Train Accuracy: 0.4319, Val Loss: 1.4974, Val Accuracy: 0.4464
Epoch 1674/10000, Train Loss: 1.4974, Train Accuracy: 0.4442, Val Loss: 1.4972, Val Accuracy: 0.4464
Epoch 1675/10000, Train Loss: 1.4936, Train Accuracy: 0.4431, Val Loss: 1.4971, Val Accuracy: 0.4464
Epoch 1676/10000, Train Loss: 1.4967, Train Accuracy: 0.4230, Val Loss: 1.4969, Val Accuracy: 0.4464
Epoch 1677/10000, Train Loss: 1.4968, Train Accuracy: 0.4252, Val Loss: 1.4968, Val Accuracy: 0.4464
Epoch 1678/10000, Train Loss: 1.4956, Train Accuracy: 0.4408, Val Loss: 1.4965, Val Accuracy: 0.4509
Epoch 1679/10000, Train Loss: 1.4932, Train Accuracy: 0.4420, Val Loss: 1.4964, Val Accuracy: 0.4464
Epoch 1680/10000, Train Loss: 1.4933, Train Accuracy: 0.4554, Val Loss: 1.4962, Val Accuracy: 0.4464
Epoch 1681/10000, Train Loss: 1.4965, Train Accuracy: 0.4397, Val Loss: 1.4960, Val Accuracy: 0.4509
Epoch 1682/10000, Train Loss: 1.4927, Train Accuracy: 0.4319, Val Loss: 1.4959, Val Accuracy: 0.4509
Epoch 1683/10000, Train Loss: 1.4961, Train Accuracy: 0.4286, Val Loss: 1.4957, Val Accuracy: 0.4509
Epoch 1684/10000, Train Loss: 1.4914, Train Accuracy: 0.4319, Val Loss: 1.4955, Val Accuracy: 0.4509
Epoch 1685/10000, Train Loss: 1.4963, Train Accuracy: 0.4286, Val Loss: 1.4954, Val Accuracy: 0.4509
Epoch 1686/10000, Train Loss: 1.4903, Train Accuracy: 0.4342, Val Loss: 1.4953, Val Accuracy: 0.4509
Epoch 1687/10000, Train Loss: 1.4892, Train Accuracy: 0.4308, Val Loss: 1.4951, Val Accuracy: 0.4509
Epoch 1688/10000, Train Loss: 1.4909, Train Accuracy: 0.4397, Val Loss: 1.4949, Val Accuracy: 0.4509
Epoch 1689/10000, Train Loss: 1.4916, Train Accuracy: 0.4375, Val Loss: 1.4947, Val Accuracy: 0.4509
Epoch 1690/10000, Train Loss: 1.4925, Train Accuracy: 0.4464, Val Loss: 1.4945, Val Accuracy: 0.4509
Epoch 1691/10000, Train Loss: 1.4920, Train Accuracy: 0.4520, Val Loss: 1.4944, Val Accuracy: 0.4554
Epoch 1692/10000, Train Loss: 1.4901, Train Accuracy: 0.4397, Val Loss: 1.4942, Val Accuracy: 0.4554
Epoch 1693/10000, Train Loss: 1.4895, Train Accuracy: 0.4442, Val Loss: 1.4940, Val Accuracy: 0.4554
Epoch 1694/10000, Train Loss: 1.4920, Train Accuracy: 0.4531, Val Loss: 1.4938, Val Accuracy: 0.4554
Epoch 1695/10000, Train Loss: 1.4899, Train Accuracy: 0.4397, Val Loss: 1.4937, Val Accuracy: 0.4554
Epoch 1696/10000, Train Loss: 1.4956, Train Accuracy: 0.4498, Val Loss: 1.4936, Val Accuracy: 0.4554
Epoch 1697/10000, Train Loss: 1.4911, Train Accuracy: 0.4353, Val Loss: 1.4934, Val Accuracy: 0.4554
Epoch 1698/10000, Train Loss: 1.4884, Train Accuracy: 0.4464, Val Loss: 1.4933, Val Accuracy: 0.4554
Epoch 1699/10000, Train Loss: 1.4889, Train Accuracy: 0.4475, Val Loss: 1.4931, Val Accuracy: 0.4554
Epoch 1700/10000, Train Loss: 1.4882, Train Accuracy: 0.4353, Val Loss: 1.4930, Val Accuracy: 0.4554
Epoch 1701/10000, Train Loss: 1.4917, Train Accuracy: 0.4420, Val Loss: 1.4928, Val Accuracy: 0.4554
Epoch 1702/10000, Train Loss: 1.4902, Train Accuracy: 0.4386, Val Loss: 1.4927, Val Accuracy: 0.4554
Epoch 1703/10000, Train Loss: 1.4891, Train Accuracy: 0.4464, Val Loss: 1.4925, Val Accuracy: 0.4554
Epoch 1704/10000, Train Loss: 1.4906, Train Accuracy: 0.4353, Val Loss: 1.4924, Val Accuracy: 0.4554
Epoch 1705/10000, Train Loss: 1.4868, Train Accuracy: 0.4554, Val Loss: 1.4922, Val Accuracy: 0.4509
Epoch 1706/10000, Train Loss: 1.4921, Train Accuracy: 0.4152, Val Loss: 1.4920, Val Accuracy: 0.4554
Epoch 1707/10000, Train Loss: 1.4890, Train Accuracy: 0.4375, Val Loss: 1.4919, Val Accuracy: 0.4509
Epoch 1708/10000, Train Loss: 1.4891, Train Accuracy: 0.4330, Val Loss: 1.4916, Val Accuracy: 0.4554
Epoch 1709/10000, Train Loss: 1.4925, Train Accuracy: 0.4397, Val Loss: 1.4915, Val Accuracy: 0.4554
Epoch 1710/10000, Train Loss: 1.4917, Train Accuracy: 0.4420, Val Loss: 1.4914, Val Accuracy: 0.4554
Epoch 1711/10000, Train Loss: 1.4899, Train Accuracy: 0.4263, Val Loss: 1.4911, Val Accuracy: 0.4554
Epoch 1712/10000, Train Loss: 1.4872, Train Accuracy: 0.4297, Val Loss: 1.4910, Val Accuracy: 0.4509
Epoch 1713/10000, Train Loss: 1.4865, Train Accuracy: 0.4487, Val Loss: 1.4909, Val Accuracy: 0.4509
Epoch 1714/10000, Train Loss: 1.4863, Train Accuracy: 0.4520, Val Loss: 1.4907, Val Accuracy: 0.4509
Epoch 1715/10000, Train Loss: 1.4924, Train Accuracy: 0.4420, Val Loss: 1.4905, Val Accuracy: 0.4509
Epoch 1716/10000, Train Loss: 1.4857, Train Accuracy: 0.4375, Val Loss: 1.4903, Val Accuracy: 0.4509
Epoch 1717/10000, Train Loss: 1.4857, Train Accuracy: 0.4386, Val Loss: 1.4902, Val Accuracy: 0.4509
Epoch 1718/10000, Train Loss: 1.4866, Train Accuracy: 0.4286, Val Loss: 1.4901, Val Accuracy: 0.4554
Epoch 1719/10000, Train Loss: 1.4849, Train Accuracy: 0.4565, Val Loss: 1.4899, Val Accuracy: 0.4554
Epoch 1720/10000, Train Loss: 1.4864, Train Accuracy: 0.4397, Val Loss: 1.4897, Val Accuracy: 0.4554
Epoch 1721/10000, Train Loss: 1.4892, Train Accuracy: 0.4275, Val Loss: 1.4895, Val Accuracy: 0.4554
Epoch 1722/10000, Train Loss: 1.4863, Train Accuracy: 0.4375, Val Loss: 1.4894, Val Accuracy: 0.4554
Epoch 1723/10000, Train Loss: 1.4940, Train Accuracy: 0.4275, Val Loss: 1.4892, Val Accuracy: 0.4554
Epoch 1724/10000, Train Loss: 1.4840, Train Accuracy: 0.4297, Val Loss: 1.4891, Val Accuracy: 0.4554
Epoch 1725/10000, Train Loss: 1.4839, Train Accuracy: 0.4565, Val Loss: 1.4890, Val Accuracy: 0.4554
Epoch 1726/10000, Train Loss: 1.4825, Train Accuracy: 0.4509, Val Loss: 1.4889, Val Accuracy: 0.4554
Epoch 1727/10000, Train Loss: 1.4850, Train Accuracy: 0.4464, Val Loss: 1.4887, Val Accuracy: 0.4554
Epoch 1728/10000, Train Loss: 1.4841, Train Accuracy: 0.4442, Val Loss: 1.4885, Val Accuracy: 0.4554
Epoch 1729/10000, Train Loss: 1.4829, Train Accuracy: 0.4442, Val Loss: 1.4884, Val Accuracy: 0.4554
Epoch 1730/10000, Train Loss: 1.4860, Train Accuracy: 0.4308, Val Loss: 1.4883, Val Accuracy: 0.4554
Epoch 1731/10000, Train Loss: 1.4898, Train Accuracy: 0.4275, Val Loss: 1.4881, Val Accuracy: 0.4554
Epoch 1732/10000, Train Loss: 1.4831, Train Accuracy: 0.4453, Val Loss: 1.4880, Val Accuracy: 0.4554
Epoch 1733/10000, Train Loss: 1.4822, Train Accuracy: 0.4364, Val Loss: 1.4878, Val Accuracy: 0.4554
Epoch 1734/10000, Train Loss: 1.4883, Train Accuracy: 0.4263, Val Loss: 1.4877, Val Accuracy: 0.4554
Epoch 1735/10000, Train Loss: 1.4830, Train Accuracy: 0.4464, Val Loss: 1.4875, Val Accuracy: 0.4554
Epoch 1736/10000, Train Loss: 1.4869, Train Accuracy: 0.4475, Val Loss: 1.4874, Val Accuracy: 0.4554
Epoch 1737/10000, Train Loss: 1.4872, Train Accuracy: 0.4342, Val Loss: 1.4872, Val Accuracy: 0.4554
Epoch 1738/10000, Train Loss: 1.4891, Train Accuracy: 0.4420, Val Loss: 1.4870, Val Accuracy: 0.4554
Epoch 1739/10000, Train Loss: 1.4838, Train Accuracy: 0.4475, Val Loss: 1.4869, Val Accuracy: 0.4554
Epoch 1740/10000, Train Loss: 1.4860, Train Accuracy: 0.4487, Val Loss: 1.4867, Val Accuracy: 0.4554
Epoch 1741/10000, Train Loss: 1.4889, Train Accuracy: 0.4397, Val Loss: 1.4866, Val Accuracy: 0.4554
Epoch 1742/10000, Train Loss: 1.4842, Train Accuracy: 0.4442, Val Loss: 1.4864, Val Accuracy: 0.4554
Epoch 1743/10000, Train Loss: 1.4826, Train Accuracy: 0.4609, Val Loss: 1.4862, Val Accuracy: 0.4554
Epoch 1744/10000, Train Loss: 1.4804, Train Accuracy: 0.4498, Val Loss: 1.4861, Val Accuracy: 0.4598
Epoch 1745/10000, Train Loss: 1.4810, Train Accuracy: 0.4397, Val Loss: 1.4859, Val Accuracy: 0.4598
Epoch 1746/10000, Train Loss: 1.4835, Train Accuracy: 0.4386, Val Loss: 1.4857, Val Accuracy: 0.4598
Epoch 1747/10000, Train Loss: 1.4790, Train Accuracy: 0.4542, Val Loss: 1.4855, Val Accuracy: 0.4598
Epoch 1748/10000, Train Loss: 1.4827, Train Accuracy: 0.4654, Val Loss: 1.4853, Val Accuracy: 0.4598
Epoch 1749/10000, Train Loss: 1.4850, Train Accuracy: 0.4308, Val Loss: 1.4852, Val Accuracy: 0.4598
Epoch 1750/10000, Train Loss: 1.4811, Train Accuracy: 0.4431, Val Loss: 1.4850, Val Accuracy: 0.4598
Epoch 1751/10000, Train Loss: 1.4836, Train Accuracy: 0.4487, Val Loss: 1.4849, Val Accuracy: 0.4598
Epoch 1752/10000, Train Loss: 1.4811, Train Accuracy: 0.4587, Val Loss: 1.4847, Val Accuracy: 0.4598
Epoch 1753/10000, Train Loss: 1.4775, Train Accuracy: 0.4431, Val Loss: 1.4845, Val Accuracy: 0.4598
Epoch 1754/10000, Train Loss: 1.4818, Train Accuracy: 0.4330, Val Loss: 1.4844, Val Accuracy: 0.4598
Epoch 1755/10000, Train Loss: 1.4851, Train Accuracy: 0.4375, Val Loss: 1.4843, Val Accuracy: 0.4598
Epoch 1756/10000, Train Loss: 1.4775, Train Accuracy: 0.4475, Val Loss: 1.4841, Val Accuracy: 0.4598
Epoch 1757/10000, Train Loss: 1.4778, Train Accuracy: 0.4420, Val Loss: 1.4840, Val Accuracy: 0.4598
Epoch 1758/10000, Train Loss: 1.4760, Train Accuracy: 0.4565, Val Loss: 1.4839, Val Accuracy: 0.4598
Epoch 1759/10000, Train Loss: 1.4808, Train Accuracy: 0.4442, Val Loss: 1.4837, Val Accuracy: 0.4598
Epoch 1760/10000, Train Loss: 1.4780, Train Accuracy: 0.4587, Val Loss: 1.4836, Val Accuracy: 0.4598
Epoch 1761/10000, Train Loss: 1.4850, Train Accuracy: 0.4364, Val Loss: 1.4834, Val Accuracy: 0.4598
Epoch 1762/10000, Train Loss: 1.4810, Train Accuracy: 0.4342, Val Loss: 1.4832, Val Accuracy: 0.4598
Epoch 1763/10000, Train Loss: 1.4766, Train Accuracy: 0.4464, Val Loss: 1.4831, Val Accuracy: 0.4598
Epoch 1764/10000, Train Loss: 1.4792, Train Accuracy: 0.4542, Val Loss: 1.4829, Val Accuracy: 0.4598
Epoch 1765/10000, Train Loss: 1.4759, Train Accuracy: 0.4643, Val Loss: 1.4828, Val Accuracy: 0.4598
Epoch 1766/10000, Train Loss: 1.4740, Train Accuracy: 0.4475, Val Loss: 1.4827, Val Accuracy: 0.4598
Epoch 1767/10000, Train Loss: 1.4753, Train Accuracy: 0.4520, Val Loss: 1.4825, Val Accuracy: 0.4598
Epoch 1768/10000, Train Loss: 1.4840, Train Accuracy: 0.4397, Val Loss: 1.4823, Val Accuracy: 0.4598
Epoch 1769/10000, Train Loss: 1.4787, Train Accuracy: 0.4509, Val Loss: 1.4822, Val Accuracy: 0.4598
Epoch 1770/10000, Train Loss: 1.4764, Train Accuracy: 0.4576, Val Loss: 1.4820, Val Accuracy: 0.4598
Epoch 1771/10000, Train Loss: 1.4772, Train Accuracy: 0.4342, Val Loss: 1.4819, Val Accuracy: 0.4598
Epoch 1772/10000, Train Loss: 1.4780, Train Accuracy: 0.4386, Val Loss: 1.4818, Val Accuracy: 0.4598
Epoch 1773/10000, Train Loss: 1.4775, Train Accuracy: 0.4554, Val Loss: 1.4816, Val Accuracy: 0.4598
Epoch 1774/10000, Train Loss: 1.4822, Train Accuracy: 0.4442, Val Loss: 1.4814, Val Accuracy: 0.4598
Epoch 1775/10000, Train Loss: 1.4778, Train Accuracy: 0.4487, Val Loss: 1.4812, Val Accuracy: 0.4598
Epoch 1776/10000, Train Loss: 1.4787, Train Accuracy: 0.4531, Val Loss: 1.4811, Val Accuracy: 0.4598
Epoch 1777/10000, Train Loss: 1.4719, Train Accuracy: 0.4676, Val Loss: 1.4810, Val Accuracy: 0.4598
Epoch 1778/10000, Train Loss: 1.4777, Train Accuracy: 0.4475, Val Loss: 1.4808, Val Accuracy: 0.4598
Epoch 1779/10000, Train Loss: 1.4782, Train Accuracy: 0.4442, Val Loss: 1.4807, Val Accuracy: 0.4598
Epoch 1780/10000, Train Loss: 1.4764, Train Accuracy: 0.4654, Val Loss: 1.4805, Val Accuracy: 0.4598
Epoch 1781/10000, Train Loss: 1.4849, Train Accuracy: 0.4319, Val Loss: 1.4804, Val Accuracy: 0.4598
Epoch 1782/10000, Train Loss: 1.4718, Train Accuracy: 0.4609, Val Loss: 1.4803, Val Accuracy: 0.4598
Epoch 1783/10000, Train Loss: 1.4765, Train Accuracy: 0.4565, Val Loss: 1.4801, Val Accuracy: 0.4598
Epoch 1784/10000, Train Loss: 1.4743, Train Accuracy: 0.4487, Val Loss: 1.4800, Val Accuracy: 0.4598
Epoch 1785/10000, Train Loss: 1.4776, Train Accuracy: 0.4475, Val Loss: 1.4798, Val Accuracy: 0.4598
Epoch 1786/10000, Train Loss: 1.4742, Train Accuracy: 0.4464, Val Loss: 1.4796, Val Accuracy: 0.4598
Epoch 1787/10000, Train Loss: 1.4739, Train Accuracy: 0.4531, Val Loss: 1.4794, Val Accuracy: 0.4643
Epoch 1788/10000, Train Loss: 1.4735, Train Accuracy: 0.4542, Val Loss: 1.4793, Val Accuracy: 0.4643
Epoch 1789/10000, Train Loss: 1.4761, Train Accuracy: 0.4386, Val Loss: 1.4792, Val Accuracy: 0.4643
Epoch 1790/10000, Train Loss: 1.4754, Train Accuracy: 0.4509, Val Loss: 1.4791, Val Accuracy: 0.4643
Epoch 1791/10000, Train Loss: 1.4756, Train Accuracy: 0.4408, Val Loss: 1.4789, Val Accuracy: 0.4643
Epoch 1792/10000, Train Loss: 1.4726, Train Accuracy: 0.4565, Val Loss: 1.4787, Val Accuracy: 0.4643
Epoch 1793/10000, Train Loss: 1.4756, Train Accuracy: 0.4475, Val Loss: 1.4786, Val Accuracy: 0.4643
Epoch 1794/10000, Train Loss: 1.4772, Train Accuracy: 0.4509, Val Loss: 1.4785, Val Accuracy: 0.4643
Epoch 1795/10000, Train Loss: 1.4735, Train Accuracy: 0.4475, Val Loss: 1.4783, Val Accuracy: 0.4643
Epoch 1796/10000, Train Loss: 1.4738, Train Accuracy: 0.4576, Val Loss: 1.4781, Val Accuracy: 0.4643
Epoch 1797/10000, Train Loss: 1.4761, Train Accuracy: 0.4554, Val Loss: 1.4779, Val Accuracy: 0.4643
Epoch 1798/10000, Train Loss: 1.4722, Train Accuracy: 0.4721, Val Loss: 1.4778, Val Accuracy: 0.4643
Epoch 1799/10000, Train Loss: 1.4718, Train Accuracy: 0.4688, Val Loss: 1.4776, Val Accuracy: 0.4643
Epoch 1800/10000, Train Loss: 1.4795, Train Accuracy: 0.4554, Val Loss: 1.4775, Val Accuracy: 0.4732
Epoch 1801/10000, Train Loss: 1.4742, Train Accuracy: 0.4598, Val Loss: 1.4774, Val Accuracy: 0.4732
Epoch 1802/10000, Train Loss: 1.4709, Train Accuracy: 0.4453, Val Loss: 1.4772, Val Accuracy: 0.4732
Epoch 1803/10000, Train Loss: 1.4747, Train Accuracy: 0.4520, Val Loss: 1.4769, Val Accuracy: 0.4688
Epoch 1804/10000, Train Loss: 1.4721, Train Accuracy: 0.4520, Val Loss: 1.4768, Val Accuracy: 0.4732
Epoch 1805/10000, Train Loss: 1.4729, Train Accuracy: 0.4554, Val Loss: 1.4767, Val Accuracy: 0.4732
Epoch 1806/10000, Train Loss: 1.4730, Train Accuracy: 0.4554, Val Loss: 1.4765, Val Accuracy: 0.4732
Epoch 1807/10000, Train Loss: 1.4738, Train Accuracy: 0.4676, Val Loss: 1.4764, Val Accuracy: 0.4732
Epoch 1808/10000, Train Loss: 1.4722, Train Accuracy: 0.4632, Val Loss: 1.4762, Val Accuracy: 0.4732
Epoch 1809/10000, Train Loss: 1.4767, Train Accuracy: 0.4587, Val Loss: 1.4760, Val Accuracy: 0.4732
Epoch 1810/10000, Train Loss: 1.4738, Train Accuracy: 0.4319, Val Loss: 1.4759, Val Accuracy: 0.4732
Epoch 1811/10000, Train Loss: 1.4743, Train Accuracy: 0.4542, Val Loss: 1.4757, Val Accuracy: 0.4732
Epoch 1812/10000, Train Loss: 1.4704, Train Accuracy: 0.4699, Val Loss: 1.4756, Val Accuracy: 0.4732
Epoch 1813/10000, Train Loss: 1.4693, Train Accuracy: 0.4420, Val Loss: 1.4755, Val Accuracy: 0.4777
Epoch 1814/10000, Train Loss: 1.4735, Train Accuracy: 0.4286, Val Loss: 1.4753, Val Accuracy: 0.4777
Epoch 1815/10000, Train Loss: 1.4688, Train Accuracy: 0.4542, Val Loss: 1.4751, Val Accuracy: 0.4777
Epoch 1816/10000, Train Loss: 1.4688, Train Accuracy: 0.4464, Val Loss: 1.4750, Val Accuracy: 0.4777
Epoch 1817/10000, Train Loss: 1.4711, Train Accuracy: 0.4487, Val Loss: 1.4748, Val Accuracy: 0.4777
Epoch 1818/10000, Train Loss: 1.4685, Train Accuracy: 0.4643, Val Loss: 1.4747, Val Accuracy: 0.4777
Epoch 1819/10000, Train Loss: 1.4734, Train Accuracy: 0.4520, Val Loss: 1.4746, Val Accuracy: 0.4777
Epoch 1820/10000, Train Loss: 1.4693, Train Accuracy: 0.4609, Val Loss: 1.4745, Val Accuracy: 0.4777
Epoch 1821/10000, Train Loss: 1.4735, Train Accuracy: 0.4487, Val Loss: 1.4743, Val Accuracy: 0.4777
Epoch 1822/10000, Train Loss: 1.4724, Train Accuracy: 0.4665, Val Loss: 1.4742, Val Accuracy: 0.4777
Epoch 1823/10000, Train Loss: 1.4743, Train Accuracy: 0.4531, Val Loss: 1.4741, Val Accuracy: 0.4777
Epoch 1824/10000, Train Loss: 1.4730, Train Accuracy: 0.4487, Val Loss: 1.4739, Val Accuracy: 0.4777
Epoch 1825/10000, Train Loss: 1.4674, Train Accuracy: 0.4654, Val Loss: 1.4738, Val Accuracy: 0.4777
Epoch 1826/10000, Train Loss: 1.4672, Train Accuracy: 0.4542, Val Loss: 1.4736, Val Accuracy: 0.4777
Epoch 1827/10000, Train Loss: 1.4701, Train Accuracy: 0.4542, Val Loss: 1.4734, Val Accuracy: 0.4777
Epoch 1828/10000, Train Loss: 1.4682, Train Accuracy: 0.4420, Val Loss: 1.4733, Val Accuracy: 0.4777
Epoch 1829/10000, Train Loss: 1.4685, Train Accuracy: 0.4632, Val Loss: 1.4731, Val Accuracy: 0.4777
Epoch 1830/10000, Train Loss: 1.4665, Train Accuracy: 0.4688, Val Loss: 1.4729, Val Accuracy: 0.4777
Epoch 1831/10000, Train Loss: 1.4684, Train Accuracy: 0.4665, Val Loss: 1.4728, Val Accuracy: 0.4777
Epoch 1832/10000, Train Loss: 1.4702, Train Accuracy: 0.4632, Val Loss: 1.4726, Val Accuracy: 0.4821
Epoch 1833/10000, Train Loss: 1.4720, Train Accuracy: 0.4498, Val Loss: 1.4725, Val Accuracy: 0.4821
Epoch 1834/10000, Train Loss: 1.4698, Train Accuracy: 0.4520, Val Loss: 1.4723, Val Accuracy: 0.4821
Epoch 1835/10000, Train Loss: 1.4688, Train Accuracy: 0.4520, Val Loss: 1.4722, Val Accuracy: 0.4821
Epoch 1836/10000, Train Loss: 1.4675, Train Accuracy: 0.4621, Val Loss: 1.4720, Val Accuracy: 0.4821
Epoch 1837/10000, Train Loss: 1.4698, Train Accuracy: 0.4487, Val Loss: 1.4719, Val Accuracy: 0.4821
Epoch 1838/10000, Train Loss: 1.4666, Train Accuracy: 0.4598, Val Loss: 1.4717, Val Accuracy: 0.4777
Epoch 1839/10000, Train Loss: 1.4646, Train Accuracy: 0.4420, Val Loss: 1.4716, Val Accuracy: 0.4777
Epoch 1840/10000, Train Loss: 1.4648, Train Accuracy: 0.4699, Val Loss: 1.4715, Val Accuracy: 0.4777
Epoch 1841/10000, Train Loss: 1.4694, Train Accuracy: 0.4565, Val Loss: 1.4714, Val Accuracy: 0.4777
Epoch 1842/10000, Train Loss: 1.4697, Train Accuracy: 0.4665, Val Loss: 1.4712, Val Accuracy: 0.4821
Epoch 1843/10000, Train Loss: 1.4669, Train Accuracy: 0.4565, Val Loss: 1.4710, Val Accuracy: 0.4821
Epoch 1844/10000, Train Loss: 1.4653, Train Accuracy: 0.4397, Val Loss: 1.4709, Val Accuracy: 0.4821
Epoch 1845/10000, Train Loss: 1.4671, Train Accuracy: 0.4531, Val Loss: 1.4708, Val Accuracy: 0.4821
Epoch 1846/10000, Train Loss: 1.4699, Train Accuracy: 0.4587, Val Loss: 1.4706, Val Accuracy: 0.4821
Epoch 1847/10000, Train Loss: 1.4686, Train Accuracy: 0.4654, Val Loss: 1.4704, Val Accuracy: 0.4821
Epoch 1848/10000, Train Loss: 1.4633, Train Accuracy: 0.4420, Val Loss: 1.4703, Val Accuracy: 0.4866
Epoch 1849/10000, Train Loss: 1.4693, Train Accuracy: 0.4453, Val Loss: 1.4701, Val Accuracy: 0.4866
Epoch 1850/10000, Train Loss: 1.4660, Train Accuracy: 0.4509, Val Loss: 1.4700, Val Accuracy: 0.4866
Epoch 1851/10000, Train Loss: 1.4629, Train Accuracy: 0.4554, Val Loss: 1.4698, Val Accuracy: 0.4866
Epoch 1852/10000, Train Loss: 1.4639, Train Accuracy: 0.4665, Val Loss: 1.4697, Val Accuracy: 0.4866
Epoch 1853/10000, Train Loss: 1.4608, Train Accuracy: 0.4554, Val Loss: 1.4695, Val Accuracy: 0.4911
Epoch 1854/10000, Train Loss: 1.4647, Train Accuracy: 0.4420, Val Loss: 1.4694, Val Accuracy: 0.4911
Epoch 1855/10000, Train Loss: 1.4644, Train Accuracy: 0.4598, Val Loss: 1.4692, Val Accuracy: 0.4911
Epoch 1856/10000, Train Loss: 1.4687, Train Accuracy: 0.4475, Val Loss: 1.4691, Val Accuracy: 0.4911
Epoch 1857/10000, Train Loss: 1.4676, Train Accuracy: 0.4565, Val Loss: 1.4689, Val Accuracy: 0.4911
Epoch 1858/10000, Train Loss: 1.4639, Train Accuracy: 0.4453, Val Loss: 1.4688, Val Accuracy: 0.4911
Epoch 1859/10000, Train Loss: 1.4660, Train Accuracy: 0.4509, Val Loss: 1.4686, Val Accuracy: 0.4911
Epoch 1860/10000, Train Loss: 1.4652, Train Accuracy: 0.4676, Val Loss: 1.4685, Val Accuracy: 0.4911
Epoch 1861/10000, Train Loss: 1.4629, Train Accuracy: 0.4554, Val Loss: 1.4683, Val Accuracy: 0.4911
Epoch 1862/10000, Train Loss: 1.4648, Train Accuracy: 0.4542, Val Loss: 1.4682, Val Accuracy: 0.4911
Epoch 1863/10000, Train Loss: 1.4629, Train Accuracy: 0.4520, Val Loss: 1.4680, Val Accuracy: 0.4911
Epoch 1864/10000, Train Loss: 1.4676, Train Accuracy: 0.4643, Val Loss: 1.4679, Val Accuracy: 0.4911
Epoch 1865/10000, Train Loss: 1.4615, Train Accuracy: 0.4453, Val Loss: 1.4678, Val Accuracy: 0.4911
Epoch 1866/10000, Train Loss: 1.4645, Train Accuracy: 0.4587, Val Loss: 1.4676, Val Accuracy: 0.4911
Epoch 1867/10000, Train Loss: 1.4598, Train Accuracy: 0.4688, Val Loss: 1.4675, Val Accuracy: 0.4911
Epoch 1868/10000, Train Loss: 1.4624, Train Accuracy: 0.4587, Val Loss: 1.4674, Val Accuracy: 0.4911
Epoch 1869/10000, Train Loss: 1.4646, Train Accuracy: 0.4353, Val Loss: 1.4672, Val Accuracy: 0.4911
Epoch 1870/10000, Train Loss: 1.4631, Train Accuracy: 0.4587, Val Loss: 1.4671, Val Accuracy: 0.4911
Epoch 1871/10000, Train Loss: 1.4639, Train Accuracy: 0.4509, Val Loss: 1.4670, Val Accuracy: 0.4911
Epoch 1872/10000, Train Loss: 1.4582, Train Accuracy: 0.4754, Val Loss: 1.4668, Val Accuracy: 0.4911
Epoch 1873/10000, Train Loss: 1.4615, Train Accuracy: 0.4777, Val Loss: 1.4666, Val Accuracy: 0.4911
Epoch 1874/10000, Train Loss: 1.4647, Train Accuracy: 0.4632, Val Loss: 1.4665, Val Accuracy: 0.4911
Epoch 1875/10000, Train Loss: 1.4618, Train Accuracy: 0.4554, Val Loss: 1.4664, Val Accuracy: 0.4911
Epoch 1876/10000, Train Loss: 1.4606, Train Accuracy: 0.4643, Val Loss: 1.4663, Val Accuracy: 0.4911
Epoch 1877/10000, Train Loss: 1.4578, Train Accuracy: 0.4554, Val Loss: 1.4661, Val Accuracy: 0.4911
Epoch 1878/10000, Train Loss: 1.4615, Train Accuracy: 0.4766, Val Loss: 1.4660, Val Accuracy: 0.4911
Epoch 1879/10000, Train Loss: 1.4640, Train Accuracy: 0.4554, Val Loss: 1.4658, Val Accuracy: 0.4911
Epoch 1880/10000, Train Loss: 1.4655, Train Accuracy: 0.4520, Val Loss: 1.4657, Val Accuracy: 0.4911
Epoch 1881/10000, Train Loss: 1.4655, Train Accuracy: 0.4442, Val Loss: 1.4655, Val Accuracy: 0.4866
Epoch 1882/10000, Train Loss: 1.4576, Train Accuracy: 0.4509, Val Loss: 1.4654, Val Accuracy: 0.4911
Epoch 1883/10000, Train Loss: 1.4609, Train Accuracy: 0.4554, Val Loss: 1.4653, Val Accuracy: 0.4955
Epoch 1884/10000, Train Loss: 1.4595, Train Accuracy: 0.4632, Val Loss: 1.4651, Val Accuracy: 0.4911
Epoch 1885/10000, Train Loss: 1.4542, Train Accuracy: 0.4855, Val Loss: 1.4649, Val Accuracy: 0.4911
Epoch 1886/10000, Train Loss: 1.4600, Train Accuracy: 0.4576, Val Loss: 1.4647, Val Accuracy: 0.4911
Epoch 1887/10000, Train Loss: 1.4568, Train Accuracy: 0.4844, Val Loss: 1.4646, Val Accuracy: 0.4911
Epoch 1888/10000, Train Loss: 1.4592, Train Accuracy: 0.4821, Val Loss: 1.4645, Val Accuracy: 0.4911
Epoch 1889/10000, Train Loss: 1.4584, Train Accuracy: 0.4721, Val Loss: 1.4643, Val Accuracy: 0.4911
Epoch 1890/10000, Train Loss: 1.4606, Train Accuracy: 0.4665, Val Loss: 1.4641, Val Accuracy: 0.4911
Epoch 1891/10000, Train Loss: 1.4635, Train Accuracy: 0.4643, Val Loss: 1.4640, Val Accuracy: 0.4911
Epoch 1892/10000, Train Loss: 1.4562, Train Accuracy: 0.4743, Val Loss: 1.4639, Val Accuracy: 0.4955
Epoch 1893/10000, Train Loss: 1.4586, Train Accuracy: 0.4699, Val Loss: 1.4638, Val Accuracy: 0.4955
Epoch 1894/10000, Train Loss: 1.4564, Train Accuracy: 0.4632, Val Loss: 1.4637, Val Accuracy: 0.4955
Epoch 1895/10000, Train Loss: 1.4615, Train Accuracy: 0.4598, Val Loss: 1.4635, Val Accuracy: 0.4955
Epoch 1896/10000, Train Loss: 1.4604, Train Accuracy: 0.4509, Val Loss: 1.4634, Val Accuracy: 0.4955
Epoch 1897/10000, Train Loss: 1.4595, Train Accuracy: 0.4766, Val Loss: 1.4632, Val Accuracy: 0.4955
Epoch 1898/10000, Train Loss: 1.4623, Train Accuracy: 0.4453, Val Loss: 1.4631, Val Accuracy: 0.4955
Epoch 1899/10000, Train Loss: 1.4575, Train Accuracy: 0.4710, Val Loss: 1.4630, Val Accuracy: 0.4955
Epoch 1900/10000, Train Loss: 1.4611, Train Accuracy: 0.4643, Val Loss: 1.4629, Val Accuracy: 0.4955
Epoch 1901/10000, Train Loss: 1.4644, Train Accuracy: 0.4587, Val Loss: 1.4627, Val Accuracy: 0.4955
Epoch 1902/10000, Train Loss: 1.4542, Train Accuracy: 0.4911, Val Loss: 1.4626, Val Accuracy: 0.4955
Epoch 1903/10000, Train Loss: 1.4574, Train Accuracy: 0.4688, Val Loss: 1.4625, Val Accuracy: 0.4955
Epoch 1904/10000, Train Loss: 1.4560, Train Accuracy: 0.4777, Val Loss: 1.4624, Val Accuracy: 0.4955
Epoch 1905/10000, Train Loss: 1.4562, Train Accuracy: 0.4721, Val Loss: 1.4622, Val Accuracy: 0.4955
Epoch 1906/10000, Train Loss: 1.4579, Train Accuracy: 0.4542, Val Loss: 1.4620, Val Accuracy: 0.4955
Epoch 1907/10000, Train Loss: 1.4546, Train Accuracy: 0.4699, Val Loss: 1.4619, Val Accuracy: 0.4955
Epoch 1908/10000, Train Loss: 1.4523, Train Accuracy: 0.4587, Val Loss: 1.4617, Val Accuracy: 0.4955
Epoch 1909/10000, Train Loss: 1.4530, Train Accuracy: 0.4788, Val Loss: 1.4616, Val Accuracy: 0.4955
Epoch 1910/10000, Train Loss: 1.4528, Train Accuracy: 0.4788, Val Loss: 1.4614, Val Accuracy: 0.4955
Epoch 1911/10000, Train Loss: 1.4488, Train Accuracy: 0.4967, Val Loss: 1.4613, Val Accuracy: 0.4955
Epoch 1912/10000, Train Loss: 1.4550, Train Accuracy: 0.4732, Val Loss: 1.4611, Val Accuracy: 0.4955
Epoch 1913/10000, Train Loss: 1.4534, Train Accuracy: 0.4777, Val Loss: 1.4610, Val Accuracy: 0.4955
Epoch 1914/10000, Train Loss: 1.4558, Train Accuracy: 0.4453, Val Loss: 1.4609, Val Accuracy: 0.4955
Epoch 1915/10000, Train Loss: 1.4546, Train Accuracy: 0.4710, Val Loss: 1.4608, Val Accuracy: 0.4955
Epoch 1916/10000, Train Loss: 1.4604, Train Accuracy: 0.4732, Val Loss: 1.4606, Val Accuracy: 0.4955
Epoch 1917/10000, Train Loss: 1.4548, Train Accuracy: 0.4632, Val Loss: 1.4604, Val Accuracy: 0.4955
Epoch 1918/10000, Train Loss: 1.4568, Train Accuracy: 0.4688, Val Loss: 1.4603, Val Accuracy: 0.4955
Epoch 1919/10000, Train Loss: 1.4523, Train Accuracy: 0.4710, Val Loss: 1.4602, Val Accuracy: 0.4955
Epoch 1920/10000, Train Loss: 1.4490, Train Accuracy: 0.4821, Val Loss: 1.4600, Val Accuracy: 0.4955
Epoch 1921/10000, Train Loss: 1.4575, Train Accuracy: 0.4576, Val Loss: 1.4599, Val Accuracy: 0.4911
Epoch 1922/10000, Train Loss: 1.4515, Train Accuracy: 0.4688, Val Loss: 1.4598, Val Accuracy: 0.4911
Epoch 1923/10000, Train Loss: 1.4567, Train Accuracy: 0.4554, Val Loss: 1.4596, Val Accuracy: 0.4911
Epoch 1924/10000, Train Loss: 1.4574, Train Accuracy: 0.4721, Val Loss: 1.4594, Val Accuracy: 0.4911
Epoch 1925/10000, Train Loss: 1.4538, Train Accuracy: 0.4665, Val Loss: 1.4593, Val Accuracy: 0.4911
Epoch 1926/10000, Train Loss: 1.4528, Train Accuracy: 0.4654, Val Loss: 1.4591, Val Accuracy: 0.4911
Epoch 1927/10000, Train Loss: 1.4529, Train Accuracy: 0.4743, Val Loss: 1.4590, Val Accuracy: 0.4911
Epoch 1928/10000, Train Loss: 1.4542, Train Accuracy: 0.4810, Val Loss: 1.4589, Val Accuracy: 0.4911
Epoch 1929/10000, Train Loss: 1.4539, Train Accuracy: 0.4498, Val Loss: 1.4588, Val Accuracy: 0.4955
Epoch 1930/10000, Train Loss: 1.4533, Train Accuracy: 0.4710, Val Loss: 1.4587, Val Accuracy: 0.4955
Epoch 1931/10000, Train Loss: 1.4509, Train Accuracy: 0.4721, Val Loss: 1.4585, Val Accuracy: 0.4911
Epoch 1932/10000, Train Loss: 1.4474, Train Accuracy: 0.4844, Val Loss: 1.4584, Val Accuracy: 0.4955
Epoch 1933/10000, Train Loss: 1.4486, Train Accuracy: 0.4833, Val Loss: 1.4583, Val Accuracy: 0.4955
Epoch 1934/10000, Train Loss: 1.4493, Train Accuracy: 0.4676, Val Loss: 1.4581, Val Accuracy: 0.4955
Epoch 1935/10000, Train Loss: 1.4560, Train Accuracy: 0.4732, Val Loss: 1.4580, Val Accuracy: 0.4955
Epoch 1936/10000, Train Loss: 1.4548, Train Accuracy: 0.4710, Val Loss: 1.4579, Val Accuracy: 0.4955
Epoch 1937/10000, Train Loss: 1.4500, Train Accuracy: 0.4732, Val Loss: 1.4576, Val Accuracy: 0.4955
Epoch 1938/10000, Train Loss: 1.4496, Train Accuracy: 0.4766, Val Loss: 1.4574, Val Accuracy: 0.5000
Epoch 1939/10000, Train Loss: 1.4489, Train Accuracy: 0.4844, Val Loss: 1.4572, Val Accuracy: 0.5000
Epoch 1940/10000, Train Loss: 1.4510, Train Accuracy: 0.4743, Val Loss: 1.4572, Val Accuracy: 0.4955
Epoch 1941/10000, Train Loss: 1.4470, Train Accuracy: 0.4955, Val Loss: 1.4570, Val Accuracy: 0.5000
Epoch 1942/10000, Train Loss: 1.4533, Train Accuracy: 0.4710, Val Loss: 1.4569, Val Accuracy: 0.5000
Epoch 1943/10000, Train Loss: 1.4524, Train Accuracy: 0.4699, Val Loss: 1.4568, Val Accuracy: 0.5000
Epoch 1944/10000, Train Loss: 1.4497, Train Accuracy: 0.4598, Val Loss: 1.4567, Val Accuracy: 0.5000
Epoch 1945/10000, Train Loss: 1.4538, Train Accuracy: 0.4777, Val Loss: 1.4566, Val Accuracy: 0.5000
Epoch 1946/10000, Train Loss: 1.4568, Train Accuracy: 0.4598, Val Loss: 1.4564, Val Accuracy: 0.5000
Epoch 1947/10000, Train Loss: 1.4485, Train Accuracy: 0.4788, Val Loss: 1.4563, Val Accuracy: 0.5000
Epoch 1948/10000, Train Loss: 1.4520, Train Accuracy: 0.4754, Val Loss: 1.4561, Val Accuracy: 0.5000
Epoch 1949/10000, Train Loss: 1.4500, Train Accuracy: 0.4900, Val Loss: 1.4560, Val Accuracy: 0.5000
Epoch 1950/10000, Train Loss: 1.4519, Train Accuracy: 0.4810, Val Loss: 1.4559, Val Accuracy: 0.5000
Epoch 1951/10000, Train Loss: 1.4532, Train Accuracy: 0.4900, Val Loss: 1.4558, Val Accuracy: 0.5000
Epoch 1952/10000, Train Loss: 1.4484, Train Accuracy: 0.4978, Val Loss: 1.4557, Val Accuracy: 0.5000
Epoch 1953/10000, Train Loss: 1.4505, Train Accuracy: 0.4866, Val Loss: 1.4555, Val Accuracy: 0.5000
Epoch 1954/10000, Train Loss: 1.4533, Train Accuracy: 0.4766, Val Loss: 1.4553, Val Accuracy: 0.5000
Epoch 1955/10000, Train Loss: 1.4537, Train Accuracy: 0.4609, Val Loss: 1.4552, Val Accuracy: 0.5000
Epoch 1956/10000, Train Loss: 1.4500, Train Accuracy: 0.4844, Val Loss: 1.4551, Val Accuracy: 0.5000
Epoch 1957/10000, Train Loss: 1.4551, Train Accuracy: 0.4688, Val Loss: 1.4550, Val Accuracy: 0.5000
Epoch 1958/10000, Train Loss: 1.4504, Train Accuracy: 0.4732, Val Loss: 1.4548, Val Accuracy: 0.5000
Epoch 1959/10000, Train Loss: 1.4535, Train Accuracy: 0.4621, Val Loss: 1.4547, Val Accuracy: 0.5000
Epoch 1960/10000, Train Loss: 1.4513, Train Accuracy: 0.4732, Val Loss: 1.4546, Val Accuracy: 0.5000
Epoch 1961/10000, Train Loss: 1.4482, Train Accuracy: 0.4676, Val Loss: 1.4544, Val Accuracy: 0.5000
Epoch 1962/10000, Train Loss: 1.4499, Train Accuracy: 0.4866, Val Loss: 1.4543, Val Accuracy: 0.5000
Epoch 1963/10000, Train Loss: 1.4565, Train Accuracy: 0.4643, Val Loss: 1.4542, Val Accuracy: 0.5000
Epoch 1964/10000, Train Loss: 1.4533, Train Accuracy: 0.4877, Val Loss: 1.4541, Val Accuracy: 0.5045
Epoch 1965/10000, Train Loss: 1.4500, Train Accuracy: 0.4621, Val Loss: 1.4539, Val Accuracy: 0.5045
Epoch 1966/10000, Train Loss: 1.4502, Train Accuracy: 0.4844, Val Loss: 1.4538, Val Accuracy: 0.5045
Epoch 1967/10000, Train Loss: 1.4487, Train Accuracy: 0.4922, Val Loss: 1.4537, Val Accuracy: 0.5045
Epoch 1968/10000, Train Loss: 1.4446, Train Accuracy: 0.4766, Val Loss: 1.4536, Val Accuracy: 0.5045
Epoch 1969/10000, Train Loss: 1.4485, Train Accuracy: 0.4788, Val Loss: 1.4534, Val Accuracy: 0.5045
Epoch 1970/10000, Train Loss: 1.4501, Train Accuracy: 0.4754, Val Loss: 1.4533, Val Accuracy: 0.5045
Epoch 1971/10000, Train Loss: 1.4474, Train Accuracy: 0.4833, Val Loss: 1.4532, Val Accuracy: 0.5045
Epoch 1972/10000, Train Loss: 1.4455, Train Accuracy: 0.4855, Val Loss: 1.4530, Val Accuracy: 0.5045
Epoch 1973/10000, Train Loss: 1.4488, Train Accuracy: 0.4833, Val Loss: 1.4530, Val Accuracy: 0.5045
Epoch 1974/10000, Train Loss: 1.4552, Train Accuracy: 0.4721, Val Loss: 1.4528, Val Accuracy: 0.5045
Epoch 1975/10000, Train Loss: 1.4490, Train Accuracy: 0.4676, Val Loss: 1.4527, Val Accuracy: 0.5045
Epoch 1976/10000, Train Loss: 1.4466, Train Accuracy: 0.4821, Val Loss: 1.4525, Val Accuracy: 0.5045
Epoch 1977/10000, Train Loss: 1.4386, Train Accuracy: 0.5000, Val Loss: 1.4524, Val Accuracy: 0.5000
Epoch 1978/10000, Train Loss: 1.4431, Train Accuracy: 0.4911, Val Loss: 1.4522, Val Accuracy: 0.5000
Epoch 1979/10000, Train Loss: 1.4456, Train Accuracy: 0.4866, Val Loss: 1.4521, Val Accuracy: 0.5000
Epoch 1980/10000, Train Loss: 1.4420, Train Accuracy: 0.4877, Val Loss: 1.4520, Val Accuracy: 0.5000
Epoch 1981/10000, Train Loss: 1.4467, Train Accuracy: 0.4944, Val Loss: 1.4519, Val Accuracy: 0.5000
Epoch 1982/10000, Train Loss: 1.4467, Train Accuracy: 0.4821, Val Loss: 1.4517, Val Accuracy: 0.5000
Epoch 1983/10000, Train Loss: 1.4456, Train Accuracy: 0.5011, Val Loss: 1.4515, Val Accuracy: 0.5000
Epoch 1984/10000, Train Loss: 1.4449, Train Accuracy: 0.4777, Val Loss: 1.4514, Val Accuracy: 0.5000
Epoch 1985/10000, Train Loss: 1.4470, Train Accuracy: 0.4799, Val Loss: 1.4513, Val Accuracy: 0.5045
Epoch 1986/10000, Train Loss: 1.4484, Train Accuracy: 0.4810, Val Loss: 1.4512, Val Accuracy: 0.5045
Epoch 1987/10000, Train Loss: 1.4464, Train Accuracy: 0.4732, Val Loss: 1.4510, Val Accuracy: 0.5045
Epoch 1988/10000, Train Loss: 1.4449, Train Accuracy: 0.4967, Val Loss: 1.4509, Val Accuracy: 0.5045
Epoch 1989/10000, Train Loss: 1.4432, Train Accuracy: 0.5000, Val Loss: 1.4507, Val Accuracy: 0.5045
Epoch 1990/10000, Train Loss: 1.4446, Train Accuracy: 0.4933, Val Loss: 1.4506, Val Accuracy: 0.5045
Epoch 1991/10000, Train Loss: 1.4422, Train Accuracy: 0.4833, Val Loss: 1.4505, Val Accuracy: 0.5045
Epoch 1992/10000, Train Loss: 1.4402, Train Accuracy: 0.5078, Val Loss: 1.4503, Val Accuracy: 0.5045
Epoch 1993/10000, Train Loss: 1.4426, Train Accuracy: 0.4732, Val Loss: 1.4502, Val Accuracy: 0.5045
Epoch 1994/10000, Train Loss: 1.4401, Train Accuracy: 0.5033, Val Loss: 1.4500, Val Accuracy: 0.5045
Epoch 1995/10000, Train Loss: 1.4414, Train Accuracy: 0.4933, Val Loss: 1.4499, Val Accuracy: 0.5045
Epoch 1996/10000, Train Loss: 1.4421, Train Accuracy: 0.4955, Val Loss: 1.4498, Val Accuracy: 0.5045
Epoch 1997/10000, Train Loss: 1.4454, Train Accuracy: 0.4944, Val Loss: 1.4496, Val Accuracy: 0.5045
Epoch 1998/10000, Train Loss: 1.4442, Train Accuracy: 0.4877, Val Loss: 1.4494, Val Accuracy: 0.5045
Epoch 1999/10000, Train Loss: 1.4471, Train Accuracy: 0.4888, Val Loss: 1.4494, Val Accuracy: 0.5045
Epoch 2000/10000, Train Loss: 1.4421, Train Accuracy: 0.4900, Val Loss: 1.4493, Val Accuracy: 0.5089
Epoch 2001/10000, Train Loss: 1.4453, Train Accuracy: 0.4732, Val Loss: 1.4492, Val Accuracy: 0.5089
Epoch 2002/10000, Train Loss: 1.4431, Train Accuracy: 0.4721, Val Loss: 1.4490, Val Accuracy: 0.5089
Epoch 2003/10000, Train Loss: 1.4496, Train Accuracy: 0.4766, Val Loss: 1.4489, Val Accuracy: 0.5089
Epoch 2004/10000, Train Loss: 1.4437, Train Accuracy: 0.4710, Val Loss: 1.4487, Val Accuracy: 0.5089
Epoch 2005/10000, Train Loss: 1.4396, Train Accuracy: 0.4821, Val Loss: 1.4486, Val Accuracy: 0.5089
Epoch 2006/10000, Train Loss: 1.4449, Train Accuracy: 0.4833, Val Loss: 1.4485, Val Accuracy: 0.5089
Epoch 2007/10000, Train Loss: 1.4405, Train Accuracy: 0.4944, Val Loss: 1.4484, Val Accuracy: 0.5045
Epoch 2008/10000, Train Loss: 1.4403, Train Accuracy: 0.5123, Val Loss: 1.4483, Val Accuracy: 0.5045
Epoch 2009/10000, Train Loss: 1.4429, Train Accuracy: 0.4788, Val Loss: 1.4481, Val Accuracy: 0.5045
Epoch 2010/10000, Train Loss: 1.4452, Train Accuracy: 0.4565, Val Loss: 1.4480, Val Accuracy: 0.5045
Epoch 2011/10000, Train Loss: 1.4394, Train Accuracy: 0.4799, Val Loss: 1.4479, Val Accuracy: 0.5045
Epoch 2012/10000, Train Loss: 1.4438, Train Accuracy: 0.4866, Val Loss: 1.4477, Val Accuracy: 0.5045
Epoch 2013/10000, Train Loss: 1.4419, Train Accuracy: 0.4944, Val Loss: 1.4476, Val Accuracy: 0.5045
Epoch 2014/10000, Train Loss: 1.4416, Train Accuracy: 0.4933, Val Loss: 1.4475, Val Accuracy: 0.5045
Epoch 2015/10000, Train Loss: 1.4398, Train Accuracy: 0.4766, Val Loss: 1.4473, Val Accuracy: 0.5045
Epoch 2016/10000, Train Loss: 1.4377, Train Accuracy: 0.4855, Val Loss: 1.4472, Val Accuracy: 0.5045
Epoch 2017/10000, Train Loss: 1.4393, Train Accuracy: 0.5156, Val Loss: 1.4471, Val Accuracy: 0.5045
Epoch 2018/10000, Train Loss: 1.4432, Train Accuracy: 0.4877, Val Loss: 1.4470, Val Accuracy: 0.5045
Epoch 2019/10000, Train Loss: 1.4420, Train Accuracy: 0.5011, Val Loss: 1.4468, Val Accuracy: 0.5045
Epoch 2020/10000, Train Loss: 1.4394, Train Accuracy: 0.4810, Val Loss: 1.4467, Val Accuracy: 0.5045
Epoch 2021/10000, Train Loss: 1.4351, Train Accuracy: 0.4989, Val Loss: 1.4466, Val Accuracy: 0.5045
Epoch 2022/10000, Train Loss: 1.4352, Train Accuracy: 0.4978, Val Loss: 1.4464, Val Accuracy: 0.5045
Epoch 2023/10000, Train Loss: 1.4388, Train Accuracy: 0.5022, Val Loss: 1.4463, Val Accuracy: 0.5045
Epoch 2024/10000, Train Loss: 1.4374, Train Accuracy: 0.4877, Val Loss: 1.4462, Val Accuracy: 0.5045
Epoch 2025/10000, Train Loss: 1.4414, Train Accuracy: 0.4777, Val Loss: 1.4460, Val Accuracy: 0.5045
Epoch 2026/10000, Train Loss: 1.4426, Train Accuracy: 0.4866, Val Loss: 1.4459, Val Accuracy: 0.5045
Epoch 2027/10000, Train Loss: 1.4410, Train Accuracy: 0.4877, Val Loss: 1.4457, Val Accuracy: 0.5045
Epoch 2028/10000, Train Loss: 1.4365, Train Accuracy: 0.4955, Val Loss: 1.4456, Val Accuracy: 0.5045
Epoch 2029/10000, Train Loss: 1.4391, Train Accuracy: 0.4922, Val Loss: 1.4454, Val Accuracy: 0.5045
Epoch 2030/10000, Train Loss: 1.4370, Train Accuracy: 0.5145, Val Loss: 1.4453, Val Accuracy: 0.5045
Epoch 2031/10000, Train Loss: 1.4391, Train Accuracy: 0.5067, Val Loss: 1.4452, Val Accuracy: 0.5045
Epoch 2032/10000, Train Loss: 1.4389, Train Accuracy: 0.4877, Val Loss: 1.4451, Val Accuracy: 0.5045
Epoch 2033/10000, Train Loss: 1.4353, Train Accuracy: 0.4978, Val Loss: 1.4450, Val Accuracy: 0.5045
Epoch 2034/10000, Train Loss: 1.4346, Train Accuracy: 0.4922, Val Loss: 1.4449, Val Accuracy: 0.5045
Epoch 2035/10000, Train Loss: 1.4366, Train Accuracy: 0.5045, Val Loss: 1.4447, Val Accuracy: 0.5045
Epoch 2036/10000, Train Loss: 1.4357, Train Accuracy: 0.4978, Val Loss: 1.4446, Val Accuracy: 0.5045
Epoch 2037/10000, Train Loss: 1.4345, Train Accuracy: 0.4989, Val Loss: 1.4445, Val Accuracy: 0.5045
Epoch 2038/10000, Train Loss: 1.4402, Train Accuracy: 0.4866, Val Loss: 1.4444, Val Accuracy: 0.5045
Epoch 2039/10000, Train Loss: 1.4391, Train Accuracy: 0.4967, Val Loss: 1.4443, Val Accuracy: 0.5045
Epoch 2040/10000, Train Loss: 1.4410, Train Accuracy: 0.4978, Val Loss: 1.4441, Val Accuracy: 0.5045
Epoch 2041/10000, Train Loss: 1.4362, Train Accuracy: 0.5067, Val Loss: 1.4440, Val Accuracy: 0.5000
Epoch 2042/10000, Train Loss: 1.4338, Train Accuracy: 0.5056, Val Loss: 1.4439, Val Accuracy: 0.5000
Epoch 2043/10000, Train Loss: 1.4400, Train Accuracy: 0.4866, Val Loss: 1.4438, Val Accuracy: 0.5000
Epoch 2044/10000, Train Loss: 1.4343, Train Accuracy: 0.5112, Val Loss: 1.4436, Val Accuracy: 0.5045
Epoch 2045/10000, Train Loss: 1.4366, Train Accuracy: 0.4989, Val Loss: 1.4436, Val Accuracy: 0.5045
Epoch 2046/10000, Train Loss: 1.4336, Train Accuracy: 0.5134, Val Loss: 1.4434, Val Accuracy: 0.5045
Epoch 2047/10000, Train Loss: 1.4362, Train Accuracy: 0.5179, Val Loss: 1.4433, Val Accuracy: 0.5000
Epoch 2048/10000, Train Loss: 1.4344, Train Accuracy: 0.4900, Val Loss: 1.4432, Val Accuracy: 0.5045
Epoch 2049/10000, Train Loss: 1.4377, Train Accuracy: 0.5234, Val Loss: 1.4431, Val Accuracy: 0.5045
Epoch 2050/10000, Train Loss: 1.4358, Train Accuracy: 0.4944, Val Loss: 1.4430, Val Accuracy: 0.5045
Epoch 2051/10000, Train Loss: 1.4391, Train Accuracy: 0.4833, Val Loss: 1.4428, Val Accuracy: 0.5089
Epoch 2052/10000, Train Loss: 1.4281, Train Accuracy: 0.5112, Val Loss: 1.4427, Val Accuracy: 0.5089
Epoch 2053/10000, Train Loss: 1.4350, Train Accuracy: 0.5000, Val Loss: 1.4424, Val Accuracy: 0.5089
Epoch 2054/10000, Train Loss: 1.4373, Train Accuracy: 0.5022, Val Loss: 1.4423, Val Accuracy: 0.5089
Epoch 2055/10000, Train Loss: 1.4401, Train Accuracy: 0.5078, Val Loss: 1.4422, Val Accuracy: 0.5045
Epoch 2056/10000, Train Loss: 1.4387, Train Accuracy: 0.5033, Val Loss: 1.4421, Val Accuracy: 0.5089
Epoch 2057/10000, Train Loss: 1.4298, Train Accuracy: 0.5145, Val Loss: 1.4419, Val Accuracy: 0.5045
Epoch 2058/10000, Train Loss: 1.4340, Train Accuracy: 0.4967, Val Loss: 1.4417, Val Accuracy: 0.5089
Epoch 2059/10000, Train Loss: 1.4353, Train Accuracy: 0.5156, Val Loss: 1.4416, Val Accuracy: 0.5134
Epoch 2060/10000, Train Loss: 1.4371, Train Accuracy: 0.5123, Val Loss: 1.4415, Val Accuracy: 0.5134
Epoch 2061/10000, Train Loss: 1.4344, Train Accuracy: 0.4922, Val Loss: 1.4414, Val Accuracy: 0.5089
Epoch 2062/10000, Train Loss: 1.4351, Train Accuracy: 0.4911, Val Loss: 1.4413, Val Accuracy: 0.5089
Epoch 2063/10000, Train Loss: 1.4314, Train Accuracy: 0.5167, Val Loss: 1.4412, Val Accuracy: 0.5134
Epoch 2064/10000, Train Loss: 1.4313, Train Accuracy: 0.5078, Val Loss: 1.4411, Val Accuracy: 0.5134
Epoch 2065/10000, Train Loss: 1.4351, Train Accuracy: 0.5022, Val Loss: 1.4409, Val Accuracy: 0.5134
Epoch 2066/10000, Train Loss: 1.4319, Train Accuracy: 0.5156, Val Loss: 1.4408, Val Accuracy: 0.5134
Epoch 2067/10000, Train Loss: 1.4417, Train Accuracy: 0.4799, Val Loss: 1.4407, Val Accuracy: 0.5134
Epoch 2068/10000, Train Loss: 1.4326, Train Accuracy: 0.5056, Val Loss: 1.4406, Val Accuracy: 0.5134
Epoch 2069/10000, Train Loss: 1.4340, Train Accuracy: 0.5011, Val Loss: 1.4405, Val Accuracy: 0.5134
Epoch 2070/10000, Train Loss: 1.4321, Train Accuracy: 0.5056, Val Loss: 1.4404, Val Accuracy: 0.5134
Epoch 2071/10000, Train Loss: 1.4358, Train Accuracy: 0.5067, Val Loss: 1.4402, Val Accuracy: 0.5134
Epoch 2072/10000, Train Loss: 1.4284, Train Accuracy: 0.5234, Val Loss: 1.4401, Val Accuracy: 0.5134
Epoch 2073/10000, Train Loss: 1.4265, Train Accuracy: 0.5179, Val Loss: 1.4400, Val Accuracy: 0.5134
Epoch 2074/10000, Train Loss: 1.4360, Train Accuracy: 0.5067, Val Loss: 1.4398, Val Accuracy: 0.5134
Epoch 2075/10000, Train Loss: 1.4307, Train Accuracy: 0.5201, Val Loss: 1.4397, Val Accuracy: 0.5134
Epoch 2076/10000, Train Loss: 1.4316, Train Accuracy: 0.5100, Val Loss: 1.4396, Val Accuracy: 0.5134
Epoch 2077/10000, Train Loss: 1.4297, Train Accuracy: 0.5190, Val Loss: 1.4395, Val Accuracy: 0.5134
Epoch 2078/10000, Train Loss: 1.4325, Train Accuracy: 0.5011, Val Loss: 1.4394, Val Accuracy: 0.5134
Epoch 2079/10000, Train Loss: 1.4295, Train Accuracy: 0.4967, Val Loss: 1.4392, Val Accuracy: 0.5134
Epoch 2080/10000, Train Loss: 1.4368, Train Accuracy: 0.4989, Val Loss: 1.4391, Val Accuracy: 0.5134
Epoch 2081/10000, Train Loss: 1.4228, Train Accuracy: 0.5290, Val Loss: 1.4390, Val Accuracy: 0.5134
Epoch 2082/10000, Train Loss: 1.4296, Train Accuracy: 0.5246, Val Loss: 1.4389, Val Accuracy: 0.5134
Epoch 2083/10000, Train Loss: 1.4259, Train Accuracy: 0.5201, Val Loss: 1.4388, Val Accuracy: 0.5134
Epoch 2084/10000, Train Loss: 1.4290, Train Accuracy: 0.5011, Val Loss: 1.4387, Val Accuracy: 0.5134
Epoch 2085/10000, Train Loss: 1.4284, Train Accuracy: 0.5100, Val Loss: 1.4387, Val Accuracy: 0.5134
Epoch 2086/10000, Train Loss: 1.4298, Train Accuracy: 0.5167, Val Loss: 1.4385, Val Accuracy: 0.5134
Epoch 2087/10000, Train Loss: 1.4280, Train Accuracy: 0.5123, Val Loss: 1.4384, Val Accuracy: 0.5134
Epoch 2088/10000, Train Loss: 1.4244, Train Accuracy: 0.5190, Val Loss: 1.4382, Val Accuracy: 0.5134
Epoch 2089/10000, Train Loss: 1.4282, Train Accuracy: 0.5223, Val Loss: 1.4381, Val Accuracy: 0.5134
Epoch 2090/10000, Train Loss: 1.4302, Train Accuracy: 0.4933, Val Loss: 1.4380, Val Accuracy: 0.5134
Epoch 2091/10000, Train Loss: 1.4281, Train Accuracy: 0.5112, Val Loss: 1.4378, Val Accuracy: 0.5134
Epoch 2092/10000, Train Loss: 1.4298, Train Accuracy: 0.5011, Val Loss: 1.4377, Val Accuracy: 0.5179
Epoch 2093/10000, Train Loss: 1.4373, Train Accuracy: 0.5000, Val Loss: 1.4376, Val Accuracy: 0.5179
Epoch 2094/10000, Train Loss: 1.4270, Train Accuracy: 0.5089, Val Loss: 1.4375, Val Accuracy: 0.5179
Epoch 2095/10000, Train Loss: 1.4306, Train Accuracy: 0.5056, Val Loss: 1.4373, Val Accuracy: 0.5179
Epoch 2096/10000, Train Loss: 1.4253, Train Accuracy: 0.5045, Val Loss: 1.4372, Val Accuracy: 0.5179
Epoch 2097/10000, Train Loss: 1.4287, Train Accuracy: 0.5123, Val Loss: 1.4371, Val Accuracy: 0.5179
Epoch 2098/10000, Train Loss: 1.4235, Train Accuracy: 0.5379, Val Loss: 1.4369, Val Accuracy: 0.5179
Epoch 2099/10000, Train Loss: 1.4295, Train Accuracy: 0.4978, Val Loss: 1.4368, Val Accuracy: 0.5223
Epoch 2100/10000, Train Loss: 1.4273, Train Accuracy: 0.4978, Val Loss: 1.4367, Val Accuracy: 0.5268
Epoch 2101/10000, Train Loss: 1.4250, Train Accuracy: 0.5100, Val Loss: 1.4366, Val Accuracy: 0.5268
Epoch 2102/10000, Train Loss: 1.4274, Train Accuracy: 0.5067, Val Loss: 1.4364, Val Accuracy: 0.5268
Epoch 2103/10000, Train Loss: 1.4286, Train Accuracy: 0.5056, Val Loss: 1.4362, Val Accuracy: 0.5223
Epoch 2104/10000, Train Loss: 1.4303, Train Accuracy: 0.5145, Val Loss: 1.4362, Val Accuracy: 0.5223
Epoch 2105/10000, Train Loss: 1.4300, Train Accuracy: 0.5089, Val Loss: 1.4361, Val Accuracy: 0.5223
Epoch 2106/10000, Train Loss: 1.4278, Train Accuracy: 0.5223, Val Loss: 1.4360, Val Accuracy: 0.5268
Epoch 2107/10000, Train Loss: 1.4243, Train Accuracy: 0.5089, Val Loss: 1.4358, Val Accuracy: 0.5268
Epoch 2108/10000, Train Loss: 1.4248, Train Accuracy: 0.5067, Val Loss: 1.4357, Val Accuracy: 0.5268
Epoch 2109/10000, Train Loss: 1.4274, Train Accuracy: 0.5112, Val Loss: 1.4356, Val Accuracy: 0.5268
Epoch 2110/10000, Train Loss: 1.4245, Train Accuracy: 0.5145, Val Loss: 1.4354, Val Accuracy: 0.5223
Epoch 2111/10000, Train Loss: 1.4262, Train Accuracy: 0.5156, Val Loss: 1.4353, Val Accuracy: 0.5223
Epoch 2112/10000, Train Loss: 1.4283, Train Accuracy: 0.5045, Val Loss: 1.4352, Val Accuracy: 0.5223
Epoch 2113/10000, Train Loss: 1.4307, Train Accuracy: 0.5145, Val Loss: 1.4350, Val Accuracy: 0.5223
Epoch 2114/10000, Train Loss: 1.4268, Train Accuracy: 0.5201, Val Loss: 1.4349, Val Accuracy: 0.5223
Epoch 2115/10000, Train Loss: 1.4238, Train Accuracy: 0.5045, Val Loss: 1.4348, Val Accuracy: 0.5223
Epoch 2116/10000, Train Loss: 1.4222, Train Accuracy: 0.5246, Val Loss: 1.4347, Val Accuracy: 0.5223
Epoch 2117/10000, Train Loss: 1.4200, Train Accuracy: 0.5312, Val Loss: 1.4345, Val Accuracy: 0.5223
Epoch 2118/10000, Train Loss: 1.4195, Train Accuracy: 0.5558, Val Loss: 1.4344, Val Accuracy: 0.5223
Epoch 2119/10000, Train Loss: 1.4290, Train Accuracy: 0.5067, Val Loss: 1.4342, Val Accuracy: 0.5223
Epoch 2120/10000, Train Loss: 1.4279, Train Accuracy: 0.5033, Val Loss: 1.4341, Val Accuracy: 0.5223
Epoch 2121/10000, Train Loss: 1.4277, Train Accuracy: 0.5022, Val Loss: 1.4340, Val Accuracy: 0.5223
Epoch 2122/10000, Train Loss: 1.4232, Train Accuracy: 0.5100, Val Loss: 1.4338, Val Accuracy: 0.5223
Epoch 2123/10000, Train Loss: 1.4275, Train Accuracy: 0.5156, Val Loss: 1.4338, Val Accuracy: 0.5179
Epoch 2124/10000, Train Loss: 1.4235, Train Accuracy: 0.5223, Val Loss: 1.4336, Val Accuracy: 0.5223
Epoch 2125/10000, Train Loss: 1.4202, Train Accuracy: 0.5346, Val Loss: 1.4335, Val Accuracy: 0.5179
Epoch 2126/10000, Train Loss: 1.4264, Train Accuracy: 0.5257, Val Loss: 1.4334, Val Accuracy: 0.5179
Epoch 2127/10000, Train Loss: 1.4198, Train Accuracy: 0.5312, Val Loss: 1.4333, Val Accuracy: 0.5179
Epoch 2128/10000, Train Loss: 1.4234, Train Accuracy: 0.5234, Val Loss: 1.4331, Val Accuracy: 0.5179
Epoch 2129/10000, Train Loss: 1.4234, Train Accuracy: 0.5022, Val Loss: 1.4330, Val Accuracy: 0.5179
Epoch 2130/10000, Train Loss: 1.4281, Train Accuracy: 0.5022, Val Loss: 1.4329, Val Accuracy: 0.5179
Epoch 2131/10000, Train Loss: 1.4242, Train Accuracy: 0.5167, Val Loss: 1.4328, Val Accuracy: 0.5179
Epoch 2132/10000, Train Loss: 1.4213, Train Accuracy: 0.5446, Val Loss: 1.4327, Val Accuracy: 0.5223
Epoch 2133/10000, Train Loss: 1.4278, Train Accuracy: 0.4978, Val Loss: 1.4326, Val Accuracy: 0.5223
Epoch 2134/10000, Train Loss: 1.4226, Train Accuracy: 0.5246, Val Loss: 1.4324, Val Accuracy: 0.5223
Epoch 2135/10000, Train Loss: 1.4274, Train Accuracy: 0.5045, Val Loss: 1.4323, Val Accuracy: 0.5179
Epoch 2136/10000, Train Loss: 1.4156, Train Accuracy: 0.5223, Val Loss: 1.4322, Val Accuracy: 0.5179
Epoch 2137/10000, Train Loss: 1.4204, Train Accuracy: 0.5279, Val Loss: 1.4321, Val Accuracy: 0.5179
Epoch 2138/10000, Train Loss: 1.4238, Train Accuracy: 0.5279, Val Loss: 1.4319, Val Accuracy: 0.5179
Epoch 2139/10000, Train Loss: 1.4278, Train Accuracy: 0.5145, Val Loss: 1.4318, Val Accuracy: 0.5223
Epoch 2140/10000, Train Loss: 1.4248, Train Accuracy: 0.5279, Val Loss: 1.4316, Val Accuracy: 0.5179
Epoch 2141/10000, Train Loss: 1.4282, Train Accuracy: 0.5145, Val Loss: 1.4315, Val Accuracy: 0.5179
Epoch 2142/10000, Train Loss: 1.4280, Train Accuracy: 0.5212, Val Loss: 1.4315, Val Accuracy: 0.5179
Epoch 2143/10000, Train Loss: 1.4209, Train Accuracy: 0.5246, Val Loss: 1.4314, Val Accuracy: 0.5134
Epoch 2144/10000, Train Loss: 1.4218, Train Accuracy: 0.5357, Val Loss: 1.4313, Val Accuracy: 0.5134
Epoch 2145/10000, Train Loss: 1.4169, Train Accuracy: 0.5279, Val Loss: 1.4312, Val Accuracy: 0.5134
Epoch 2146/10000, Train Loss: 1.4173, Train Accuracy: 0.5402, Val Loss: 1.4311, Val Accuracy: 0.5134
Epoch 2147/10000, Train Loss: 1.4282, Train Accuracy: 0.5056, Val Loss: 1.4310, Val Accuracy: 0.5134
Epoch 2148/10000, Train Loss: 1.4173, Train Accuracy: 0.5324, Val Loss: 1.4309, Val Accuracy: 0.5179
Epoch 2149/10000, Train Loss: 1.4224, Train Accuracy: 0.5312, Val Loss: 1.4307, Val Accuracy: 0.5134
Epoch 2150/10000, Train Loss: 1.4233, Train Accuracy: 0.5134, Val Loss: 1.4306, Val Accuracy: 0.5134
Epoch 2151/10000, Train Loss: 1.4214, Train Accuracy: 0.5246, Val Loss: 1.4305, Val Accuracy: 0.5134
Epoch 2152/10000, Train Loss: 1.4165, Train Accuracy: 0.5357, Val Loss: 1.4304, Val Accuracy: 0.5134
Epoch 2153/10000, Train Loss: 1.4162, Train Accuracy: 0.5257, Val Loss: 1.4303, Val Accuracy: 0.5134
Epoch 2154/10000, Train Loss: 1.4177, Train Accuracy: 0.5234, Val Loss: 1.4301, Val Accuracy: 0.5134
Epoch 2155/10000, Train Loss: 1.4209, Train Accuracy: 0.5134, Val Loss: 1.4300, Val Accuracy: 0.5134
Epoch 2156/10000, Train Loss: 1.4213, Train Accuracy: 0.5190, Val Loss: 1.4298, Val Accuracy: 0.5089
Epoch 2157/10000, Train Loss: 1.4121, Train Accuracy: 0.5368, Val Loss: 1.4297, Val Accuracy: 0.5089
Epoch 2158/10000, Train Loss: 1.4219, Train Accuracy: 0.5357, Val Loss: 1.4296, Val Accuracy: 0.5089
Epoch 2159/10000, Train Loss: 1.4318, Train Accuracy: 0.4978, Val Loss: 1.4295, Val Accuracy: 0.5089
Epoch 2160/10000, Train Loss: 1.4200, Train Accuracy: 0.5201, Val Loss: 1.4293, Val Accuracy: 0.5089
Epoch 2161/10000, Train Loss: 1.4220, Train Accuracy: 0.5145, Val Loss: 1.4291, Val Accuracy: 0.5089
Epoch 2162/10000, Train Loss: 1.4205, Train Accuracy: 0.5223, Val Loss: 1.4290, Val Accuracy: 0.5089
Epoch 2163/10000, Train Loss: 1.4164, Train Accuracy: 0.5335, Val Loss: 1.4287, Val Accuracy: 0.5089
Epoch 2164/10000, Train Loss: 1.4221, Train Accuracy: 0.5246, Val Loss: 1.4286, Val Accuracy: 0.5089
Epoch 2165/10000, Train Loss: 1.4147, Train Accuracy: 0.5190, Val Loss: 1.4285, Val Accuracy: 0.5089
Epoch 2166/10000, Train Loss: 1.4225, Train Accuracy: 0.5246, Val Loss: 1.4284, Val Accuracy: 0.5089
Epoch 2167/10000, Train Loss: 1.4165, Train Accuracy: 0.5357, Val Loss: 1.4284, Val Accuracy: 0.5089
Epoch 2168/10000, Train Loss: 1.4183, Train Accuracy: 0.5134, Val Loss: 1.4284, Val Accuracy: 0.5089
Epoch 2169/10000, Train Loss: 1.4142, Train Accuracy: 0.5469, Val Loss: 1.4283, Val Accuracy: 0.5089
Epoch 2170/10000, Train Loss: 1.4179, Train Accuracy: 0.5167, Val Loss: 1.4282, Val Accuracy: 0.5089
Epoch 2171/10000, Train Loss: 1.4160, Train Accuracy: 0.5190, Val Loss: 1.4280, Val Accuracy: 0.5089
Epoch 2172/10000, Train Loss: 1.4164, Train Accuracy: 0.5234, Val Loss: 1.4280, Val Accuracy: 0.5089
Epoch 2173/10000, Train Loss: 1.4142, Train Accuracy: 0.5368, Val Loss: 1.4278, Val Accuracy: 0.5089
Epoch 2174/10000, Train Loss: 1.4177, Train Accuracy: 0.5312, Val Loss: 1.4277, Val Accuracy: 0.5089
Epoch 2175/10000, Train Loss: 1.4176, Train Accuracy: 0.5212, Val Loss: 1.4276, Val Accuracy: 0.5089
Epoch 2176/10000, Train Loss: 1.4188, Train Accuracy: 0.5424, Val Loss: 1.4274, Val Accuracy: 0.5089
Epoch 2177/10000, Train Loss: 1.4146, Train Accuracy: 0.5257, Val Loss: 1.4273, Val Accuracy: 0.5089
Epoch 2178/10000, Train Loss: 1.4139, Train Accuracy: 0.5368, Val Loss: 1.4272, Val Accuracy: 0.5089
Epoch 2179/10000, Train Loss: 1.4190, Train Accuracy: 0.5134, Val Loss: 1.4271, Val Accuracy: 0.5089
Epoch 2180/10000, Train Loss: 1.4202, Train Accuracy: 0.5201, Val Loss: 1.4270, Val Accuracy: 0.5089
Epoch 2181/10000, Train Loss: 1.4175, Train Accuracy: 0.5223, Val Loss: 1.4269, Val Accuracy: 0.5089
Epoch 2182/10000, Train Loss: 1.4151, Train Accuracy: 0.5223, Val Loss: 1.4267, Val Accuracy: 0.5089
Epoch 2183/10000, Train Loss: 1.4169, Train Accuracy: 0.5201, Val Loss: 1.4267, Val Accuracy: 0.5089
Epoch 2184/10000, Train Loss: 1.4231, Train Accuracy: 0.5022, Val Loss: 1.4266, Val Accuracy: 0.5089
Epoch 2185/10000, Train Loss: 1.4130, Train Accuracy: 0.5234, Val Loss: 1.4264, Val Accuracy: 0.5089
Epoch 2186/10000, Train Loss: 1.4194, Train Accuracy: 0.5145, Val Loss: 1.4263, Val Accuracy: 0.5089
Epoch 2187/10000, Train Loss: 1.4159, Train Accuracy: 0.5502, Val Loss: 1.4262, Val Accuracy: 0.5089
Epoch 2188/10000, Train Loss: 1.4193, Train Accuracy: 0.5134, Val Loss: 1.4261, Val Accuracy: 0.5089
Epoch 2189/10000, Train Loss: 1.4167, Train Accuracy: 0.5190, Val Loss: 1.4260, Val Accuracy: 0.5089
Epoch 2190/10000, Train Loss: 1.4141, Train Accuracy: 0.5212, Val Loss: 1.4259, Val Accuracy: 0.5089
Epoch 2191/10000, Train Loss: 1.4211, Train Accuracy: 0.5167, Val Loss: 1.4257, Val Accuracy: 0.5089
Epoch 2192/10000, Train Loss: 1.4174, Train Accuracy: 0.5357, Val Loss: 1.4256, Val Accuracy: 0.5089
Epoch 2193/10000, Train Loss: 1.4167, Train Accuracy: 0.5223, Val Loss: 1.4255, Val Accuracy: 0.5089
Epoch 2194/10000, Train Loss: 1.4128, Train Accuracy: 0.5446, Val Loss: 1.4254, Val Accuracy: 0.5089
Epoch 2195/10000, Train Loss: 1.4191, Train Accuracy: 0.5379, Val Loss: 1.4253, Val Accuracy: 0.5089
Epoch 2196/10000, Train Loss: 1.4115, Train Accuracy: 0.5167, Val Loss: 1.4252, Val Accuracy: 0.5089
Epoch 2197/10000, Train Loss: 1.4110, Train Accuracy: 0.5469, Val Loss: 1.4251, Val Accuracy: 0.5089
Epoch 2198/10000, Train Loss: 1.4092, Train Accuracy: 0.5212, Val Loss: 1.4249, Val Accuracy: 0.5089
Epoch 2199/10000, Train Loss: 1.4051, Train Accuracy: 0.5502, Val Loss: 1.4249, Val Accuracy: 0.5089
Epoch 2200/10000, Train Loss: 1.4156, Train Accuracy: 0.5402, Val Loss: 1.4248, Val Accuracy: 0.5089
Epoch 2201/10000, Train Loss: 1.4110, Train Accuracy: 0.5391, Val Loss: 1.4246, Val Accuracy: 0.5089
Epoch 2202/10000, Train Loss: 1.4114, Train Accuracy: 0.5469, Val Loss: 1.4246, Val Accuracy: 0.5089
Epoch 2203/10000, Train Loss: 1.4162, Train Accuracy: 0.5301, Val Loss: 1.4245, Val Accuracy: 0.5089
Epoch 2204/10000, Train Loss: 1.4143, Train Accuracy: 0.5212, Val Loss: 1.4244, Val Accuracy: 0.5089
Epoch 2205/10000, Train Loss: 1.4113, Train Accuracy: 0.5368, Val Loss: 1.4242, Val Accuracy: 0.5089
Epoch 2206/10000, Train Loss: 1.4097, Train Accuracy: 0.5491, Val Loss: 1.4240, Val Accuracy: 0.5089
Epoch 2207/10000, Train Loss: 1.4107, Train Accuracy: 0.5413, Val Loss: 1.4239, Val Accuracy: 0.5089
Epoch 2208/10000, Train Loss: 1.4097, Train Accuracy: 0.5279, Val Loss: 1.4238, Val Accuracy: 0.5134
Epoch 2209/10000, Train Loss: 1.4177, Train Accuracy: 0.5246, Val Loss: 1.4237, Val Accuracy: 0.5134
Epoch 2210/10000, Train Loss: 1.4127, Train Accuracy: 0.5335, Val Loss: 1.4236, Val Accuracy: 0.5134
Epoch 2211/10000, Train Loss: 1.4126, Train Accuracy: 0.5469, Val Loss: 1.4234, Val Accuracy: 0.5089
Epoch 2212/10000, Train Loss: 1.4160, Train Accuracy: 0.5190, Val Loss: 1.4234, Val Accuracy: 0.5134
Epoch 2213/10000, Train Loss: 1.4122, Train Accuracy: 0.5424, Val Loss: 1.4232, Val Accuracy: 0.5134
Epoch 2214/10000, Train Loss: 1.4083, Train Accuracy: 0.5469, Val Loss: 1.4231, Val Accuracy: 0.5134
Epoch 2215/10000, Train Loss: 1.4096, Train Accuracy: 0.5391, Val Loss: 1.4230, Val Accuracy: 0.5134
Epoch 2216/10000, Train Loss: 1.4063, Train Accuracy: 0.5368, Val Loss: 1.4228, Val Accuracy: 0.5134
Epoch 2217/10000, Train Loss: 1.4192, Train Accuracy: 0.5257, Val Loss: 1.4227, Val Accuracy: 0.5134
Epoch 2218/10000, Train Loss: 1.4060, Train Accuracy: 0.5446, Val Loss: 1.4226, Val Accuracy: 0.5134
Epoch 2219/10000, Train Loss: 1.4128, Train Accuracy: 0.5469, Val Loss: 1.4225, Val Accuracy: 0.5134
Epoch 2220/10000, Train Loss: 1.4101, Train Accuracy: 0.5357, Val Loss: 1.4224, Val Accuracy: 0.5134
Epoch 2221/10000, Train Loss: 1.4100, Train Accuracy: 0.5502, Val Loss: 1.4223, Val Accuracy: 0.5134
Epoch 2222/10000, Train Loss: 1.4128, Train Accuracy: 0.5257, Val Loss: 1.4222, Val Accuracy: 0.5179
Epoch 2223/10000, Train Loss: 1.4086, Train Accuracy: 0.5335, Val Loss: 1.4221, Val Accuracy: 0.5179
Epoch 2224/10000, Train Loss: 1.4125, Train Accuracy: 0.5312, Val Loss: 1.4219, Val Accuracy: 0.5179
Epoch 2225/10000, Train Loss: 1.4091, Train Accuracy: 0.5491, Val Loss: 1.4218, Val Accuracy: 0.5179
Epoch 2226/10000, Train Loss: 1.4102, Train Accuracy: 0.5469, Val Loss: 1.4217, Val Accuracy: 0.5179
Epoch 2227/10000, Train Loss: 1.4094, Train Accuracy: 0.5357, Val Loss: 1.4216, Val Accuracy: 0.5179
Epoch 2228/10000, Train Loss: 1.4113, Train Accuracy: 0.5536, Val Loss: 1.4214, Val Accuracy: 0.5179
Epoch 2229/10000, Train Loss: 1.4085, Train Accuracy: 0.5469, Val Loss: 1.4214, Val Accuracy: 0.5179
Epoch 2230/10000, Train Loss: 1.4067, Train Accuracy: 0.5413, Val Loss: 1.4212, Val Accuracy: 0.5179
Epoch 2231/10000, Train Loss: 1.4017, Train Accuracy: 0.5357, Val Loss: 1.4211, Val Accuracy: 0.5179
Epoch 2232/10000, Train Loss: 1.4046, Train Accuracy: 0.5469, Val Loss: 1.4210, Val Accuracy: 0.5179
Epoch 2233/10000, Train Loss: 1.4000, Train Accuracy: 0.5569, Val Loss: 1.4209, Val Accuracy: 0.5179
Epoch 2234/10000, Train Loss: 1.4087, Train Accuracy: 0.5413, Val Loss: 1.4208, Val Accuracy: 0.5179
Epoch 2235/10000, Train Loss: 1.4028, Train Accuracy: 0.5446, Val Loss: 1.4206, Val Accuracy: 0.5179
Epoch 2236/10000, Train Loss: 1.4113, Train Accuracy: 0.5167, Val Loss: 1.4206, Val Accuracy: 0.5179
Epoch 2237/10000, Train Loss: 1.4072, Train Accuracy: 0.5290, Val Loss: 1.4205, Val Accuracy: 0.5179
Epoch 2238/10000, Train Loss: 1.4129, Train Accuracy: 0.5324, Val Loss: 1.4204, Val Accuracy: 0.5179
Epoch 2239/10000, Train Loss: 1.4097, Train Accuracy: 0.5513, Val Loss: 1.4203, Val Accuracy: 0.5223
Epoch 2240/10000, Train Loss: 1.4100, Train Accuracy: 0.5368, Val Loss: 1.4201, Val Accuracy: 0.5179
Epoch 2241/10000, Train Loss: 1.4111, Train Accuracy: 0.5312, Val Loss: 1.4200, Val Accuracy: 0.5179
Epoch 2242/10000, Train Loss: 1.4173, Train Accuracy: 0.5134, Val Loss: 1.4199, Val Accuracy: 0.5223
Epoch 2243/10000, Train Loss: 1.4091, Train Accuracy: 0.5435, Val Loss: 1.4198, Val Accuracy: 0.5223
Epoch 2244/10000, Train Loss: 1.4068, Train Accuracy: 0.5491, Val Loss: 1.4196, Val Accuracy: 0.5223
Epoch 2245/10000, Train Loss: 1.4105, Train Accuracy: 0.5446, Val Loss: 1.4195, Val Accuracy: 0.5223
Epoch 2246/10000, Train Loss: 1.4092, Train Accuracy: 0.5335, Val Loss: 1.4195, Val Accuracy: 0.5223
Epoch 2247/10000, Train Loss: 1.4067, Train Accuracy: 0.5234, Val Loss: 1.4194, Val Accuracy: 0.5223
Epoch 2248/10000, Train Loss: 1.4096, Train Accuracy: 0.5223, Val Loss: 1.4192, Val Accuracy: 0.5223
Epoch 2249/10000, Train Loss: 1.4071, Train Accuracy: 0.5435, Val Loss: 1.4192, Val Accuracy: 0.5268
Epoch 2250/10000, Train Loss: 1.4089, Train Accuracy: 0.5536, Val Loss: 1.4191, Val Accuracy: 0.5268
Epoch 2251/10000, Train Loss: 1.4079, Train Accuracy: 0.5402, Val Loss: 1.4190, Val Accuracy: 0.5268
Epoch 2252/10000, Train Loss: 1.4069, Train Accuracy: 0.5335, Val Loss: 1.4189, Val Accuracy: 0.5268
Epoch 2253/10000, Train Loss: 1.4007, Train Accuracy: 0.5714, Val Loss: 1.4188, Val Accuracy: 0.5268
Epoch 2254/10000, Train Loss: 1.4027, Train Accuracy: 0.5502, Val Loss: 1.4187, Val Accuracy: 0.5223
Epoch 2255/10000, Train Loss: 1.4031, Train Accuracy: 0.5525, Val Loss: 1.4186, Val Accuracy: 0.5223
Epoch 2256/10000, Train Loss: 1.4107, Train Accuracy: 0.5246, Val Loss: 1.4185, Val Accuracy: 0.5223
Epoch 2257/10000, Train Loss: 1.4055, Train Accuracy: 0.5290, Val Loss: 1.4184, Val Accuracy: 0.5223
Epoch 2258/10000, Train Loss: 1.4054, Train Accuracy: 0.5536, Val Loss: 1.4183, Val Accuracy: 0.5223
Epoch 2259/10000, Train Loss: 1.4022, Train Accuracy: 0.5480, Val Loss: 1.4181, Val Accuracy: 0.5223
Epoch 2260/10000, Train Loss: 1.4031, Train Accuracy: 0.5458, Val Loss: 1.4180, Val Accuracy: 0.5223
Epoch 2261/10000, Train Loss: 1.4087, Train Accuracy: 0.5357, Val Loss: 1.4179, Val Accuracy: 0.5223
Epoch 2262/10000, Train Loss: 1.4057, Train Accuracy: 0.5391, Val Loss: 1.4178, Val Accuracy: 0.5223
Epoch 2263/10000, Train Loss: 1.4061, Train Accuracy: 0.5424, Val Loss: 1.4177, Val Accuracy: 0.5223
Epoch 2264/10000, Train Loss: 1.4128, Train Accuracy: 0.5402, Val Loss: 1.4176, Val Accuracy: 0.5223
Epoch 2265/10000, Train Loss: 1.4019, Train Accuracy: 0.5614, Val Loss: 1.4174, Val Accuracy: 0.5223
Epoch 2266/10000, Train Loss: 1.4095, Train Accuracy: 0.5246, Val Loss: 1.4173, Val Accuracy: 0.5223
Epoch 2267/10000, Train Loss: 1.4049, Train Accuracy: 0.5402, Val Loss: 1.4172, Val Accuracy: 0.5223
Epoch 2268/10000, Train Loss: 1.4023, Train Accuracy: 0.5312, Val Loss: 1.4171, Val Accuracy: 0.5223
Epoch 2269/10000, Train Loss: 1.4022, Train Accuracy: 0.5513, Val Loss: 1.4170, Val Accuracy: 0.5223
Epoch 2270/10000, Train Loss: 1.3931, Train Accuracy: 0.5636, Val Loss: 1.4168, Val Accuracy: 0.5223
Epoch 2271/10000, Train Loss: 1.4049, Train Accuracy: 0.5446, Val Loss: 1.4167, Val Accuracy: 0.5223
Epoch 2272/10000, Train Loss: 1.4039, Train Accuracy: 0.5346, Val Loss: 1.4166, Val Accuracy: 0.5223
Epoch 2273/10000, Train Loss: 1.4001, Train Accuracy: 0.5558, Val Loss: 1.4165, Val Accuracy: 0.5223
Epoch 2274/10000, Train Loss: 1.3998, Train Accuracy: 0.5603, Val Loss: 1.4164, Val Accuracy: 0.5223
Epoch 2275/10000, Train Loss: 1.4015, Train Accuracy: 0.5458, Val Loss: 1.4163, Val Accuracy: 0.5223
Epoch 2276/10000, Train Loss: 1.3956, Train Accuracy: 0.5525, Val Loss: 1.4162, Val Accuracy: 0.5223
Epoch 2277/10000, Train Loss: 1.3967, Train Accuracy: 0.5435, Val Loss: 1.4161, Val Accuracy: 0.5223
Epoch 2278/10000, Train Loss: 1.4018, Train Accuracy: 0.5357, Val Loss: 1.4160, Val Accuracy: 0.5223
Epoch 2279/10000, Train Loss: 1.3967, Train Accuracy: 0.5513, Val Loss: 1.4159, Val Accuracy: 0.5223
Epoch 2280/10000, Train Loss: 1.4043, Train Accuracy: 0.5391, Val Loss: 1.4158, Val Accuracy: 0.5223
Epoch 2281/10000, Train Loss: 1.4013, Train Accuracy: 0.5357, Val Loss: 1.4157, Val Accuracy: 0.5223
Epoch 2282/10000, Train Loss: 1.4062, Train Accuracy: 0.5513, Val Loss: 1.4156, Val Accuracy: 0.5223
Epoch 2283/10000, Train Loss: 1.3999, Train Accuracy: 0.5502, Val Loss: 1.4155, Val Accuracy: 0.5223
Epoch 2284/10000, Train Loss: 1.4006, Train Accuracy: 0.5379, Val Loss: 1.4154, Val Accuracy: 0.5268
Epoch 2285/10000, Train Loss: 1.4037, Train Accuracy: 0.5491, Val Loss: 1.4152, Val Accuracy: 0.5268
Epoch 2286/10000, Train Loss: 1.3997, Train Accuracy: 0.5547, Val Loss: 1.4151, Val Accuracy: 0.5268
Epoch 2287/10000, Train Loss: 1.4041, Train Accuracy: 0.5402, Val Loss: 1.4150, Val Accuracy: 0.5268
Epoch 2288/10000, Train Loss: 1.4025, Train Accuracy: 0.5424, Val Loss: 1.4149, Val Accuracy: 0.5268
Epoch 2289/10000, Train Loss: 1.3994, Train Accuracy: 0.5424, Val Loss: 1.4147, Val Accuracy: 0.5268
Epoch 2290/10000, Train Loss: 1.4041, Train Accuracy: 0.5379, Val Loss: 1.4146, Val Accuracy: 0.5268
Epoch 2291/10000, Train Loss: 1.4021, Train Accuracy: 0.5435, Val Loss: 1.4145, Val Accuracy: 0.5268
Epoch 2292/10000, Train Loss: 1.3992, Train Accuracy: 0.5480, Val Loss: 1.4144, Val Accuracy: 0.5268
Epoch 2293/10000, Train Loss: 1.4000, Train Accuracy: 0.5491, Val Loss: 1.4143, Val Accuracy: 0.5268
Epoch 2294/10000, Train Loss: 1.3991, Train Accuracy: 0.5502, Val Loss: 1.4142, Val Accuracy: 0.5268
Epoch 2295/10000, Train Loss: 1.3966, Train Accuracy: 0.5592, Val Loss: 1.4141, Val Accuracy: 0.5268
Epoch 2296/10000, Train Loss: 1.3966, Train Accuracy: 0.5513, Val Loss: 1.4140, Val Accuracy: 0.5268
Epoch 2297/10000, Train Loss: 1.3994, Train Accuracy: 0.5480, Val Loss: 1.4139, Val Accuracy: 0.5268
Epoch 2298/10000, Train Loss: 1.3950, Train Accuracy: 0.5513, Val Loss: 1.4138, Val Accuracy: 0.5268
Epoch 2299/10000, Train Loss: 1.4012, Train Accuracy: 0.5368, Val Loss: 1.4137, Val Accuracy: 0.5268
Epoch 2300/10000, Train Loss: 1.3978, Train Accuracy: 0.5346, Val Loss: 1.4135, Val Accuracy: 0.5223
Epoch 2301/10000, Train Loss: 1.3956, Train Accuracy: 0.5446, Val Loss: 1.4134, Val Accuracy: 0.5223
Epoch 2302/10000, Train Loss: 1.4017, Train Accuracy: 0.5402, Val Loss: 1.4132, Val Accuracy: 0.5223
Epoch 2303/10000, Train Loss: 1.4044, Train Accuracy: 0.5469, Val Loss: 1.4132, Val Accuracy: 0.5223
Epoch 2304/10000, Train Loss: 1.3929, Train Accuracy: 0.5480, Val Loss: 1.4130, Val Accuracy: 0.5223
Epoch 2305/10000, Train Loss: 1.4012, Train Accuracy: 0.5357, Val Loss: 1.4129, Val Accuracy: 0.5223
Epoch 2306/10000, Train Loss: 1.4008, Train Accuracy: 0.5502, Val Loss: 1.4128, Val Accuracy: 0.5223
Epoch 2307/10000, Train Loss: 1.3924, Train Accuracy: 0.5703, Val Loss: 1.4127, Val Accuracy: 0.5223
Epoch 2308/10000, Train Loss: 1.3967, Train Accuracy: 0.5469, Val Loss: 1.4126, Val Accuracy: 0.5223
Epoch 2309/10000, Train Loss: 1.4050, Train Accuracy: 0.5446, Val Loss: 1.4125, Val Accuracy: 0.5223
Epoch 2310/10000, Train Loss: 1.3920, Train Accuracy: 0.5759, Val Loss: 1.4123, Val Accuracy: 0.5223
Epoch 2311/10000, Train Loss: 1.3962, Train Accuracy: 0.5435, Val Loss: 1.4122, Val Accuracy: 0.5223
Epoch 2312/10000, Train Loss: 1.3972, Train Accuracy: 0.5424, Val Loss: 1.4121, Val Accuracy: 0.5223
Epoch 2313/10000, Train Loss: 1.3970, Train Accuracy: 0.5547, Val Loss: 1.4120, Val Accuracy: 0.5223
Epoch 2314/10000, Train Loss: 1.3960, Train Accuracy: 0.5324, Val Loss: 1.4119, Val Accuracy: 0.5223
Epoch 2315/10000, Train Loss: 1.4021, Train Accuracy: 0.5402, Val Loss: 1.4118, Val Accuracy: 0.5223
Epoch 2316/10000, Train Loss: 1.3985, Train Accuracy: 0.5525, Val Loss: 1.4117, Val Accuracy: 0.5223
Epoch 2317/10000, Train Loss: 1.3985, Train Accuracy: 0.5368, Val Loss: 1.4116, Val Accuracy: 0.5223
Epoch 2318/10000, Train Loss: 1.4020, Train Accuracy: 0.5513, Val Loss: 1.4115, Val Accuracy: 0.5223
Epoch 2319/10000, Train Loss: 1.3921, Train Accuracy: 0.5513, Val Loss: 1.4114, Val Accuracy: 0.5223
Epoch 2320/10000, Train Loss: 1.3977, Train Accuracy: 0.5525, Val Loss: 1.4113, Val Accuracy: 0.5223
Epoch 2321/10000, Train Loss: 1.3996, Train Accuracy: 0.5480, Val Loss: 1.4112, Val Accuracy: 0.5223
Epoch 2322/10000, Train Loss: 1.3956, Train Accuracy: 0.5435, Val Loss: 1.4110, Val Accuracy: 0.5223
Epoch 2323/10000, Train Loss: 1.4021, Train Accuracy: 0.5357, Val Loss: 1.4109, Val Accuracy: 0.5223
Epoch 2324/10000, Train Loss: 1.3950, Train Accuracy: 0.5480, Val Loss: 1.4109, Val Accuracy: 0.5223
Epoch 2325/10000, Train Loss: 1.3962, Train Accuracy: 0.5525, Val Loss: 1.4108, Val Accuracy: 0.5223
Epoch 2326/10000, Train Loss: 1.3981, Train Accuracy: 0.5458, Val Loss: 1.4107, Val Accuracy: 0.5223
Epoch 2327/10000, Train Loss: 1.3967, Train Accuracy: 0.5536, Val Loss: 1.4106, Val Accuracy: 0.5223
Epoch 2328/10000, Train Loss: 1.3994, Train Accuracy: 0.5402, Val Loss: 1.4104, Val Accuracy: 0.5223
Epoch 2329/10000, Train Loss: 1.3929, Train Accuracy: 0.5547, Val Loss: 1.4103, Val Accuracy: 0.5223
Epoch 2330/10000, Train Loss: 1.3975, Train Accuracy: 0.5491, Val Loss: 1.4102, Val Accuracy: 0.5223
Epoch 2331/10000, Train Loss: 1.3944, Train Accuracy: 0.5558, Val Loss: 1.4101, Val Accuracy: 0.5223
Epoch 2332/10000, Train Loss: 1.3926, Train Accuracy: 0.5413, Val Loss: 1.4100, Val Accuracy: 0.5179
Epoch 2333/10000, Train Loss: 1.3985, Train Accuracy: 0.5435, Val Loss: 1.4099, Val Accuracy: 0.5179
Epoch 2334/10000, Train Loss: 1.4000, Train Accuracy: 0.5212, Val Loss: 1.4098, Val Accuracy: 0.5134
Epoch 2335/10000, Train Loss: 1.3984, Train Accuracy: 0.5525, Val Loss: 1.4097, Val Accuracy: 0.5134
Epoch 2336/10000, Train Loss: 1.3973, Train Accuracy: 0.5458, Val Loss: 1.4095, Val Accuracy: 0.5134
Epoch 2337/10000, Train Loss: 1.3941, Train Accuracy: 0.5458, Val Loss: 1.4094, Val Accuracy: 0.5134
Epoch 2338/10000, Train Loss: 1.3924, Train Accuracy: 0.5536, Val Loss: 1.4093, Val Accuracy: 0.5134
Epoch 2339/10000, Train Loss: 1.3941, Train Accuracy: 0.5513, Val Loss: 1.4092, Val Accuracy: 0.5134
Epoch 2340/10000, Train Loss: 1.3976, Train Accuracy: 0.5558, Val Loss: 1.4091, Val Accuracy: 0.5134
Epoch 2341/10000, Train Loss: 1.3972, Train Accuracy: 0.5491, Val Loss: 1.4090, Val Accuracy: 0.5179
Epoch 2342/10000, Train Loss: 1.3932, Train Accuracy: 0.5402, Val Loss: 1.4090, Val Accuracy: 0.5179
Epoch 2343/10000, Train Loss: 1.3868, Train Accuracy: 0.5636, Val Loss: 1.4088, Val Accuracy: 0.5134
Epoch 2344/10000, Train Loss: 1.3952, Train Accuracy: 0.5525, Val Loss: 1.4087, Val Accuracy: 0.5134
Epoch 2345/10000, Train Loss: 1.3897, Train Accuracy: 0.5725, Val Loss: 1.4086, Val Accuracy: 0.5134
Epoch 2346/10000, Train Loss: 1.3940, Train Accuracy: 0.5458, Val Loss: 1.4085, Val Accuracy: 0.5134
Epoch 2347/10000, Train Loss: 1.3944, Train Accuracy: 0.5536, Val Loss: 1.4084, Val Accuracy: 0.5134
Epoch 2348/10000, Train Loss: 1.3879, Train Accuracy: 0.5569, Val Loss: 1.4083, Val Accuracy: 0.5134
Epoch 2349/10000, Train Loss: 1.3910, Train Accuracy: 0.5580, Val Loss: 1.4082, Val Accuracy: 0.5089
Epoch 2350/10000, Train Loss: 1.3921, Train Accuracy: 0.5446, Val Loss: 1.4081, Val Accuracy: 0.5089
Epoch 2351/10000, Train Loss: 1.3940, Train Accuracy: 0.5580, Val Loss: 1.4080, Val Accuracy: 0.5089
Epoch 2352/10000, Train Loss: 1.3907, Train Accuracy: 0.5603, Val Loss: 1.4079, Val Accuracy: 0.5089
Epoch 2353/10000, Train Loss: 1.3944, Train Accuracy: 0.5558, Val Loss: 1.4078, Val Accuracy: 0.5089
Epoch 2354/10000, Train Loss: 1.3939, Train Accuracy: 0.5391, Val Loss: 1.4076, Val Accuracy: 0.5089
Epoch 2355/10000, Train Loss: 1.3976, Train Accuracy: 0.5469, Val Loss: 1.4075, Val Accuracy: 0.5089
Epoch 2356/10000, Train Loss: 1.4003, Train Accuracy: 0.5502, Val Loss: 1.4074, Val Accuracy: 0.5134
Epoch 2357/10000, Train Loss: 1.3941, Train Accuracy: 0.5502, Val Loss: 1.4073, Val Accuracy: 0.5134
Epoch 2358/10000, Train Loss: 1.3932, Train Accuracy: 0.5592, Val Loss: 1.4072, Val Accuracy: 0.5134
Epoch 2359/10000, Train Loss: 1.3868, Train Accuracy: 0.5815, Val Loss: 1.4071, Val Accuracy: 0.5134
Epoch 2360/10000, Train Loss: 1.3910, Train Accuracy: 0.5502, Val Loss: 1.4069, Val Accuracy: 0.5134
Epoch 2361/10000, Train Loss: 1.3927, Train Accuracy: 0.5458, Val Loss: 1.4068, Val Accuracy: 0.5134
Epoch 2362/10000, Train Loss: 1.3891, Train Accuracy: 0.5670, Val Loss: 1.4067, Val Accuracy: 0.5134
Epoch 2363/10000, Train Loss: 1.3862, Train Accuracy: 0.5569, Val Loss: 1.4066, Val Accuracy: 0.5134
Epoch 2364/10000, Train Loss: 1.3862, Train Accuracy: 0.5625, Val Loss: 1.4065, Val Accuracy: 0.5089
Epoch 2365/10000, Train Loss: 1.3891, Train Accuracy: 0.5580, Val Loss: 1.4063, Val Accuracy: 0.5045
Epoch 2366/10000, Train Loss: 1.3886, Train Accuracy: 0.5692, Val Loss: 1.4063, Val Accuracy: 0.5045
Epoch 2367/10000, Train Loss: 1.3953, Train Accuracy: 0.5413, Val Loss: 1.4062, Val Accuracy: 0.5045
Epoch 2368/10000, Train Loss: 1.3889, Train Accuracy: 0.5692, Val Loss: 1.4061, Val Accuracy: 0.5089
Epoch 2369/10000, Train Loss: 1.3894, Train Accuracy: 0.5547, Val Loss: 1.4060, Val Accuracy: 0.5045
Epoch 2370/10000, Train Loss: 1.3944, Train Accuracy: 0.5413, Val Loss: 1.4059, Val Accuracy: 0.5045
Epoch 2371/10000, Train Loss: 1.3950, Train Accuracy: 0.5312, Val Loss: 1.4058, Val Accuracy: 0.5045
Epoch 2372/10000, Train Loss: 1.3910, Train Accuracy: 0.5647, Val Loss: 1.4058, Val Accuracy: 0.5045
Epoch 2373/10000, Train Loss: 1.3917, Train Accuracy: 0.5625, Val Loss: 1.4056, Val Accuracy: 0.5045
Epoch 2374/10000, Train Loss: 1.3859, Train Accuracy: 0.5681, Val Loss: 1.4055, Val Accuracy: 0.5089
Epoch 2375/10000, Train Loss: 1.3797, Train Accuracy: 0.5748, Val Loss: 1.4055, Val Accuracy: 0.5089
Epoch 2376/10000, Train Loss: 1.3888, Train Accuracy: 0.5446, Val Loss: 1.4054, Val Accuracy: 0.5089
Epoch 2377/10000, Train Loss: 1.3811, Train Accuracy: 0.5815, Val Loss: 1.4052, Val Accuracy: 0.5089
Epoch 2378/10000, Train Loss: 1.3922, Train Accuracy: 0.5536, Val Loss: 1.4051, Val Accuracy: 0.5089
Epoch 2379/10000, Train Loss: 1.3906, Train Accuracy: 0.5592, Val Loss: 1.4050, Val Accuracy: 0.5089
Epoch 2380/10000, Train Loss: 1.3883, Train Accuracy: 0.5547, Val Loss: 1.4050, Val Accuracy: 0.5089
Epoch 2381/10000, Train Loss: 1.3904, Train Accuracy: 0.5536, Val Loss: 1.4048, Val Accuracy: 0.5089
Epoch 2382/10000, Train Loss: 1.3905, Train Accuracy: 0.5391, Val Loss: 1.4048, Val Accuracy: 0.5089
Epoch 2383/10000, Train Loss: 1.3840, Train Accuracy: 0.5670, Val Loss: 1.4047, Val Accuracy: 0.5089
Epoch 2384/10000, Train Loss: 1.3876, Train Accuracy: 0.5536, Val Loss: 1.4046, Val Accuracy: 0.5089
Epoch 2385/10000, Train Loss: 1.3918, Train Accuracy: 0.5480, Val Loss: 1.4045, Val Accuracy: 0.5089
Epoch 2386/10000, Train Loss: 1.3849, Train Accuracy: 0.5759, Val Loss: 1.4044, Val Accuracy: 0.5089
Epoch 2387/10000, Train Loss: 1.3834, Train Accuracy: 0.5681, Val Loss: 1.4042, Val Accuracy: 0.5089
Epoch 2388/10000, Train Loss: 1.3871, Train Accuracy: 0.5424, Val Loss: 1.4041, Val Accuracy: 0.5089
Epoch 2389/10000, Train Loss: 1.3925, Train Accuracy: 0.5491, Val Loss: 1.4040, Val Accuracy: 0.5089
Epoch 2390/10000, Train Loss: 1.3878, Train Accuracy: 0.5480, Val Loss: 1.4039, Val Accuracy: 0.5089
Epoch 2391/10000, Train Loss: 1.3863, Train Accuracy: 0.5391, Val Loss: 1.4038, Val Accuracy: 0.5089
Epoch 2392/10000, Train Loss: 1.3851, Train Accuracy: 0.5647, Val Loss: 1.4037, Val Accuracy: 0.5089
Epoch 2393/10000, Train Loss: 1.3816, Train Accuracy: 0.5703, Val Loss: 1.4036, Val Accuracy: 0.5089
Epoch 2394/10000, Train Loss: 1.3867, Train Accuracy: 0.5469, Val Loss: 1.4035, Val Accuracy: 0.5089
Epoch 2395/10000, Train Loss: 1.3942, Train Accuracy: 0.5413, Val Loss: 1.4034, Val Accuracy: 0.5134
Epoch 2396/10000, Train Loss: 1.3774, Train Accuracy: 0.5748, Val Loss: 1.4033, Val Accuracy: 0.5134
Epoch 2397/10000, Train Loss: 1.3892, Train Accuracy: 0.5547, Val Loss: 1.4032, Val Accuracy: 0.5134
Epoch 2398/10000, Train Loss: 1.3843, Train Accuracy: 0.5547, Val Loss: 1.4031, Val Accuracy: 0.5134
Epoch 2399/10000, Train Loss: 1.3772, Train Accuracy: 0.5714, Val Loss: 1.4030, Val Accuracy: 0.5134
Epoch 2400/10000, Train Loss: 1.3863, Train Accuracy: 0.5737, Val Loss: 1.4029, Val Accuracy: 0.5134
Epoch 2401/10000, Train Loss: 1.3850, Train Accuracy: 0.5536, Val Loss: 1.4028, Val Accuracy: 0.5134
Epoch 2402/10000, Train Loss: 1.3859, Train Accuracy: 0.5580, Val Loss: 1.4027, Val Accuracy: 0.5134
Epoch 2403/10000, Train Loss: 1.3846, Train Accuracy: 0.5558, Val Loss: 1.4026, Val Accuracy: 0.5134
Epoch 2404/10000, Train Loss: 1.3855, Train Accuracy: 0.5625, Val Loss: 1.4024, Val Accuracy: 0.5134
Epoch 2405/10000, Train Loss: 1.3863, Train Accuracy: 0.5592, Val Loss: 1.4023, Val Accuracy: 0.5134
Epoch 2406/10000, Train Loss: 1.3900, Train Accuracy: 0.5592, Val Loss: 1.4022, Val Accuracy: 0.5134
Epoch 2407/10000, Train Loss: 1.3830, Train Accuracy: 0.5670, Val Loss: 1.4021, Val Accuracy: 0.5134
Epoch 2408/10000, Train Loss: 1.3795, Train Accuracy: 0.5848, Val Loss: 1.4020, Val Accuracy: 0.5134
Epoch 2409/10000, Train Loss: 1.3832, Train Accuracy: 0.5681, Val Loss: 1.4019, Val Accuracy: 0.5134
Epoch 2410/10000, Train Loss: 1.3790, Train Accuracy: 0.5681, Val Loss: 1.4018, Val Accuracy: 0.5134
Epoch 2411/10000, Train Loss: 1.3844, Train Accuracy: 0.5513, Val Loss: 1.4016, Val Accuracy: 0.5134
Epoch 2412/10000, Train Loss: 1.3926, Train Accuracy: 0.5458, Val Loss: 1.4016, Val Accuracy: 0.5134
Epoch 2413/10000, Train Loss: 1.3803, Train Accuracy: 0.5658, Val Loss: 1.4015, Val Accuracy: 0.5134
Epoch 2414/10000, Train Loss: 1.3765, Train Accuracy: 0.5703, Val Loss: 1.4014, Val Accuracy: 0.5134
Epoch 2415/10000, Train Loss: 1.3766, Train Accuracy: 0.5781, Val Loss: 1.4013, Val Accuracy: 0.5134
Epoch 2416/10000, Train Loss: 1.3820, Train Accuracy: 0.5636, Val Loss: 1.4012, Val Accuracy: 0.5134
Epoch 2417/10000, Train Loss: 1.3817, Train Accuracy: 0.5670, Val Loss: 1.4011, Val Accuracy: 0.5134
Epoch 2418/10000, Train Loss: 1.3809, Train Accuracy: 0.5670, Val Loss: 1.4009, Val Accuracy: 0.5134
Epoch 2419/10000, Train Loss: 1.3814, Train Accuracy: 0.5670, Val Loss: 1.4008, Val Accuracy: 0.5134
Epoch 2420/10000, Train Loss: 1.3876, Train Accuracy: 0.5513, Val Loss: 1.4007, Val Accuracy: 0.5134
Epoch 2421/10000, Train Loss: 1.3839, Train Accuracy: 0.5569, Val Loss: 1.4006, Val Accuracy: 0.5134
Epoch 2422/10000, Train Loss: 1.3817, Train Accuracy: 0.5603, Val Loss: 1.4005, Val Accuracy: 0.5134
Epoch 2423/10000, Train Loss: 1.3800, Train Accuracy: 0.5703, Val Loss: 1.4004, Val Accuracy: 0.5134
Epoch 2424/10000, Train Loss: 1.3721, Train Accuracy: 0.5737, Val Loss: 1.4003, Val Accuracy: 0.5134
Epoch 2425/10000, Train Loss: 1.3833, Train Accuracy: 0.5580, Val Loss: 1.4002, Val Accuracy: 0.5134
Epoch 2426/10000, Train Loss: 1.3818, Train Accuracy: 0.5681, Val Loss: 1.4001, Val Accuracy: 0.5134
Epoch 2427/10000, Train Loss: 1.3828, Train Accuracy: 0.5614, Val Loss: 1.4000, Val Accuracy: 0.5134
Epoch 2428/10000, Train Loss: 1.3871, Train Accuracy: 0.5737, Val Loss: 1.3999, Val Accuracy: 0.5134
Epoch 2429/10000, Train Loss: 1.3806, Train Accuracy: 0.5603, Val Loss: 1.3998, Val Accuracy: 0.5134
Epoch 2430/10000, Train Loss: 1.3854, Train Accuracy: 0.5737, Val Loss: 1.3997, Val Accuracy: 0.5134
Epoch 2431/10000, Train Loss: 1.3819, Train Accuracy: 0.5569, Val Loss: 1.3997, Val Accuracy: 0.5134
Epoch 2432/10000, Train Loss: 1.3856, Train Accuracy: 0.5312, Val Loss: 1.3996, Val Accuracy: 0.5134
Epoch 2433/10000, Train Loss: 1.3828, Train Accuracy: 0.5703, Val Loss: 1.3995, Val Accuracy: 0.5134
Epoch 2434/10000, Train Loss: 1.3790, Train Accuracy: 0.5692, Val Loss: 1.3994, Val Accuracy: 0.5134
Epoch 2435/10000, Train Loss: 1.3761, Train Accuracy: 0.5558, Val Loss: 1.3993, Val Accuracy: 0.5134
Epoch 2436/10000, Train Loss: 1.3749, Train Accuracy: 0.5859, Val Loss: 1.3991, Val Accuracy: 0.5134
Epoch 2437/10000, Train Loss: 1.3844, Train Accuracy: 0.5491, Val Loss: 1.3990, Val Accuracy: 0.5134
Epoch 2438/10000, Train Loss: 1.3723, Train Accuracy: 0.5770, Val Loss: 1.3989, Val Accuracy: 0.5134
Epoch 2439/10000, Train Loss: 1.3813, Train Accuracy: 0.5569, Val Loss: 1.3988, Val Accuracy: 0.5134
Epoch 2440/10000, Train Loss: 1.3837, Train Accuracy: 0.5748, Val Loss: 1.3987, Val Accuracy: 0.5134
Epoch 2441/10000, Train Loss: 1.3798, Train Accuracy: 0.5636, Val Loss: 1.3987, Val Accuracy: 0.5134
Epoch 2442/10000, Train Loss: 1.3791, Train Accuracy: 0.5792, Val Loss: 1.3986, Val Accuracy: 0.5134
Epoch 2443/10000, Train Loss: 1.3810, Train Accuracy: 0.5502, Val Loss: 1.3985, Val Accuracy: 0.5134
Epoch 2444/10000, Train Loss: 1.3748, Train Accuracy: 0.5759, Val Loss: 1.3984, Val Accuracy: 0.5134
Epoch 2445/10000, Train Loss: 1.3758, Train Accuracy: 0.5748, Val Loss: 1.3983, Val Accuracy: 0.5134
Epoch 2446/10000, Train Loss: 1.3744, Train Accuracy: 0.5714, Val Loss: 1.3982, Val Accuracy: 0.5134
Epoch 2447/10000, Train Loss: 1.3813, Train Accuracy: 0.5636, Val Loss: 1.3981, Val Accuracy: 0.5134
Epoch 2448/10000, Train Loss: 1.3781, Train Accuracy: 0.5603, Val Loss: 1.3980, Val Accuracy: 0.5134
Epoch 2449/10000, Train Loss: 1.3815, Train Accuracy: 0.5469, Val Loss: 1.3979, Val Accuracy: 0.5134
Epoch 2450/10000, Train Loss: 1.3733, Train Accuracy: 0.5792, Val Loss: 1.3979, Val Accuracy: 0.5179
Epoch 2451/10000, Train Loss: 1.3800, Train Accuracy: 0.5580, Val Loss: 1.3977, Val Accuracy: 0.5179
Epoch 2452/10000, Train Loss: 1.3806, Train Accuracy: 0.5759, Val Loss: 1.3976, Val Accuracy: 0.5179
Epoch 2453/10000, Train Loss: 1.3830, Train Accuracy: 0.5435, Val Loss: 1.3975, Val Accuracy: 0.5179
Epoch 2454/10000, Train Loss: 1.3764, Train Accuracy: 0.5636, Val Loss: 1.3975, Val Accuracy: 0.5179
Epoch 2455/10000, Train Loss: 1.3846, Train Accuracy: 0.5424, Val Loss: 1.3973, Val Accuracy: 0.5179
Epoch 2456/10000, Train Loss: 1.3758, Train Accuracy: 0.5737, Val Loss: 1.3972, Val Accuracy: 0.5179
Epoch 2457/10000, Train Loss: 1.3727, Train Accuracy: 0.5759, Val Loss: 1.3971, Val Accuracy: 0.5179
Epoch 2458/10000, Train Loss: 1.3730, Train Accuracy: 0.5859, Val Loss: 1.3970, Val Accuracy: 0.5179
Epoch 2459/10000, Train Loss: 1.3780, Train Accuracy: 0.5614, Val Loss: 1.3970, Val Accuracy: 0.5179
Epoch 2460/10000, Train Loss: 1.3727, Train Accuracy: 0.5647, Val Loss: 1.3969, Val Accuracy: 0.5179
Epoch 2461/10000, Train Loss: 1.3796, Train Accuracy: 0.5703, Val Loss: 1.3968, Val Accuracy: 0.5179
Epoch 2462/10000, Train Loss: 1.3766, Train Accuracy: 0.5647, Val Loss: 1.3967, Val Accuracy: 0.5179
Epoch 2463/10000, Train Loss: 1.3752, Train Accuracy: 0.5580, Val Loss: 1.3966, Val Accuracy: 0.5179
Epoch 2464/10000, Train Loss: 1.3740, Train Accuracy: 0.5815, Val Loss: 1.3964, Val Accuracy: 0.5179
Epoch 2465/10000, Train Loss: 1.3759, Train Accuracy: 0.5714, Val Loss: 1.3963, Val Accuracy: 0.5179
Epoch 2466/10000, Train Loss: 1.3837, Train Accuracy: 0.5692, Val Loss: 1.3962, Val Accuracy: 0.5179
Epoch 2467/10000, Train Loss: 1.3716, Train Accuracy: 0.5859, Val Loss: 1.3961, Val Accuracy: 0.5179
Epoch 2468/10000, Train Loss: 1.3767, Train Accuracy: 0.5725, Val Loss: 1.3959, Val Accuracy: 0.5179
Epoch 2469/10000, Train Loss: 1.3694, Train Accuracy: 0.5714, Val Loss: 1.3958, Val Accuracy: 0.5179
Epoch 2470/10000, Train Loss: 1.3760, Train Accuracy: 0.5592, Val Loss: 1.3957, Val Accuracy: 0.5179
Epoch 2471/10000, Train Loss: 1.3815, Train Accuracy: 0.5692, Val Loss: 1.3956, Val Accuracy: 0.5179
Epoch 2472/10000, Train Loss: 1.3695, Train Accuracy: 0.5815, Val Loss: 1.3955, Val Accuracy: 0.5179
Epoch 2473/10000, Train Loss: 1.3750, Train Accuracy: 0.5614, Val Loss: 1.3954, Val Accuracy: 0.5179
Epoch 2474/10000, Train Loss: 1.3784, Train Accuracy: 0.5804, Val Loss: 1.3953, Val Accuracy: 0.5179
Epoch 2475/10000, Train Loss: 1.3779, Train Accuracy: 0.5681, Val Loss: 1.3952, Val Accuracy: 0.5179
Epoch 2476/10000, Train Loss: 1.3773, Train Accuracy: 0.5658, Val Loss: 1.3951, Val Accuracy: 0.5179
Epoch 2477/10000, Train Loss: 1.3734, Train Accuracy: 0.5815, Val Loss: 1.3949, Val Accuracy: 0.5179
Epoch 2478/10000, Train Loss: 1.3777, Train Accuracy: 0.5703, Val Loss: 1.3948, Val Accuracy: 0.5179
Epoch 2479/10000, Train Loss: 1.3731, Train Accuracy: 0.5547, Val Loss: 1.3947, Val Accuracy: 0.5179
Epoch 2480/10000, Train Loss: 1.3755, Train Accuracy: 0.5580, Val Loss: 1.3946, Val Accuracy: 0.5179
Epoch 2481/10000, Train Loss: 1.3719, Train Accuracy: 0.5781, Val Loss: 1.3945, Val Accuracy: 0.5179
Epoch 2482/10000, Train Loss: 1.3793, Train Accuracy: 0.5737, Val Loss: 1.3944, Val Accuracy: 0.5179
Epoch 2483/10000, Train Loss: 1.3732, Train Accuracy: 0.5703, Val Loss: 1.3943, Val Accuracy: 0.5179
Epoch 2484/10000, Train Loss: 1.3775, Train Accuracy: 0.5647, Val Loss: 1.3942, Val Accuracy: 0.5179
Epoch 2485/10000, Train Loss: 1.3737, Train Accuracy: 0.5770, Val Loss: 1.3941, Val Accuracy: 0.5179
Epoch 2486/10000, Train Loss: 1.3773, Train Accuracy: 0.5759, Val Loss: 1.3940, Val Accuracy: 0.5179
Epoch 2487/10000, Train Loss: 1.3763, Train Accuracy: 0.5670, Val Loss: 1.3940, Val Accuracy: 0.5179
Epoch 2488/10000, Train Loss: 1.3715, Train Accuracy: 0.5625, Val Loss: 1.3939, Val Accuracy: 0.5179
Epoch 2489/10000, Train Loss: 1.3730, Train Accuracy: 0.5859, Val Loss: 1.3938, Val Accuracy: 0.5179
Epoch 2490/10000, Train Loss: 1.3818, Train Accuracy: 0.5603, Val Loss: 1.3937, Val Accuracy: 0.5179
Epoch 2491/10000, Train Loss: 1.3769, Train Accuracy: 0.5603, Val Loss: 1.3936, Val Accuracy: 0.5179
Epoch 2492/10000, Train Loss: 1.3688, Train Accuracy: 0.5625, Val Loss: 1.3935, Val Accuracy: 0.5179
Epoch 2493/10000, Train Loss: 1.3772, Train Accuracy: 0.5636, Val Loss: 1.3934, Val Accuracy: 0.5179
Epoch 2494/10000, Train Loss: 1.3685, Train Accuracy: 0.5971, Val Loss: 1.3933, Val Accuracy: 0.5179
Epoch 2495/10000, Train Loss: 1.3705, Train Accuracy: 0.5815, Val Loss: 1.3932, Val Accuracy: 0.5179
Epoch 2496/10000, Train Loss: 1.3783, Train Accuracy: 0.5670, Val Loss: 1.3932, Val Accuracy: 0.5179
Epoch 2497/10000, Train Loss: 1.3744, Train Accuracy: 0.5737, Val Loss: 1.3931, Val Accuracy: 0.5179
Epoch 2498/10000, Train Loss: 1.3703, Train Accuracy: 0.5725, Val Loss: 1.3930, Val Accuracy: 0.5179
Epoch 2499/10000, Train Loss: 1.3661, Train Accuracy: 0.5826, Val Loss: 1.3930, Val Accuracy: 0.5179
Epoch 2500/10000, Train Loss: 1.3739, Train Accuracy: 0.5670, Val Loss: 1.3929, Val Accuracy: 0.5179
Epoch 2501/10000, Train Loss: 1.3735, Train Accuracy: 0.5871, Val Loss: 1.3928, Val Accuracy: 0.5179
Epoch 2502/10000, Train Loss: 1.3697, Train Accuracy: 0.5725, Val Loss: 1.3927, Val Accuracy: 0.5179
Epoch 2503/10000, Train Loss: 1.3692, Train Accuracy: 0.5725, Val Loss: 1.3926, Val Accuracy: 0.5179
Epoch 2504/10000, Train Loss: 1.3727, Train Accuracy: 0.5681, Val Loss: 1.3925, Val Accuracy: 0.5179
Epoch 2505/10000, Train Loss: 1.3706, Train Accuracy: 0.5815, Val Loss: 1.3924, Val Accuracy: 0.5179
Epoch 2506/10000, Train Loss: 1.3718, Train Accuracy: 0.5681, Val Loss: 1.3923, Val Accuracy: 0.5179
Epoch 2507/10000, Train Loss: 1.3706, Train Accuracy: 0.5770, Val Loss: 1.3922, Val Accuracy: 0.5179
Epoch 2508/10000, Train Loss: 1.3694, Train Accuracy: 0.5837, Val Loss: 1.3921, Val Accuracy: 0.5179
Epoch 2509/10000, Train Loss: 1.3670, Train Accuracy: 0.5770, Val Loss: 1.3919, Val Accuracy: 0.5179
Epoch 2510/10000, Train Loss: 1.3749, Train Accuracy: 0.5681, Val Loss: 1.3918, Val Accuracy: 0.5179
Epoch 2511/10000, Train Loss: 1.3690, Train Accuracy: 0.5737, Val Loss: 1.3917, Val Accuracy: 0.5179
Epoch 2512/10000, Train Loss: 1.3682, Train Accuracy: 0.5859, Val Loss: 1.3916, Val Accuracy: 0.5179
Epoch 2513/10000, Train Loss: 1.3754, Train Accuracy: 0.5681, Val Loss: 1.3915, Val Accuracy: 0.5179
Epoch 2514/10000, Train Loss: 1.3682, Train Accuracy: 0.5737, Val Loss: 1.3915, Val Accuracy: 0.5179
Epoch 2515/10000, Train Loss: 1.3698, Train Accuracy: 0.5692, Val Loss: 1.3914, Val Accuracy: 0.5179
Epoch 2516/10000, Train Loss: 1.3743, Train Accuracy: 0.5502, Val Loss: 1.3913, Val Accuracy: 0.5179
Epoch 2517/10000, Train Loss: 1.3714, Train Accuracy: 0.5725, Val Loss: 1.3912, Val Accuracy: 0.5179
Epoch 2518/10000, Train Loss: 1.3655, Train Accuracy: 0.5781, Val Loss: 1.3911, Val Accuracy: 0.5179
Epoch 2519/10000, Train Loss: 1.3647, Train Accuracy: 0.5904, Val Loss: 1.3910, Val Accuracy: 0.5179
Epoch 2520/10000, Train Loss: 1.3668, Train Accuracy: 0.5792, Val Loss: 1.3909, Val Accuracy: 0.5179
Epoch 2521/10000, Train Loss: 1.3729, Train Accuracy: 0.5603, Val Loss: 1.3908, Val Accuracy: 0.5179
Epoch 2522/10000, Train Loss: 1.3748, Train Accuracy: 0.5458, Val Loss: 1.3908, Val Accuracy: 0.5179
Epoch 2523/10000, Train Loss: 1.3737, Train Accuracy: 0.5558, Val Loss: 1.3907, Val Accuracy: 0.5179
Epoch 2524/10000, Train Loss: 1.3725, Train Accuracy: 0.5748, Val Loss: 1.3906, Val Accuracy: 0.5179
Epoch 2525/10000, Train Loss: 1.3727, Train Accuracy: 0.5759, Val Loss: 1.3905, Val Accuracy: 0.5179
Epoch 2526/10000, Train Loss: 1.3766, Train Accuracy: 0.5469, Val Loss: 1.3904, Val Accuracy: 0.5179
Epoch 2527/10000, Train Loss: 1.3684, Train Accuracy: 0.5781, Val Loss: 1.3903, Val Accuracy: 0.5179
Epoch 2528/10000, Train Loss: 1.3652, Train Accuracy: 0.5692, Val Loss: 1.3903, Val Accuracy: 0.5179
Epoch 2529/10000, Train Loss: 1.3699, Train Accuracy: 0.5714, Val Loss: 1.3902, Val Accuracy: 0.5179
Epoch 2530/10000, Train Loss: 1.3701, Train Accuracy: 0.5792, Val Loss: 1.3901, Val Accuracy: 0.5179
Epoch 2531/10000, Train Loss: 1.3770, Train Accuracy: 0.5592, Val Loss: 1.3900, Val Accuracy: 0.5179
Epoch 2532/10000, Train Loss: 1.3632, Train Accuracy: 0.5770, Val Loss: 1.3899, Val Accuracy: 0.5179
Epoch 2533/10000, Train Loss: 1.3695, Train Accuracy: 0.5848, Val Loss: 1.3898, Val Accuracy: 0.5179
Epoch 2534/10000, Train Loss: 1.3748, Train Accuracy: 0.5580, Val Loss: 1.3897, Val Accuracy: 0.5179
Epoch 2535/10000, Train Loss: 1.3637, Train Accuracy: 0.5781, Val Loss: 1.3896, Val Accuracy: 0.5179
Epoch 2536/10000, Train Loss: 1.3645, Train Accuracy: 0.5725, Val Loss: 1.3895, Val Accuracy: 0.5179
Epoch 2537/10000, Train Loss: 1.3628, Train Accuracy: 0.5826, Val Loss: 1.3894, Val Accuracy: 0.5179
Epoch 2538/10000, Train Loss: 1.3586, Train Accuracy: 0.5871, Val Loss: 1.3892, Val Accuracy: 0.5179
Epoch 2539/10000, Train Loss: 1.3634, Train Accuracy: 0.5759, Val Loss: 1.3891, Val Accuracy: 0.5179
Epoch 2540/10000, Train Loss: 1.3698, Train Accuracy: 0.5647, Val Loss: 1.3891, Val Accuracy: 0.5179
Epoch 2541/10000, Train Loss: 1.3690, Train Accuracy: 0.5737, Val Loss: 1.3889, Val Accuracy: 0.5179
Epoch 2542/10000, Train Loss: 1.3603, Train Accuracy: 0.5915, Val Loss: 1.3888, Val Accuracy: 0.5179
Epoch 2543/10000, Train Loss: 1.3616, Train Accuracy: 0.5859, Val Loss: 1.3887, Val Accuracy: 0.5179
Epoch 2544/10000, Train Loss: 1.3671, Train Accuracy: 0.5525, Val Loss: 1.3886, Val Accuracy: 0.5179
Epoch 2545/10000, Train Loss: 1.3639, Train Accuracy: 0.5714, Val Loss: 1.3885, Val Accuracy: 0.5179
Epoch 2546/10000, Train Loss: 1.3703, Train Accuracy: 0.5647, Val Loss: 1.3885, Val Accuracy: 0.5179
Epoch 2547/10000, Train Loss: 1.3680, Train Accuracy: 0.5692, Val Loss: 1.3884, Val Accuracy: 0.5179
Epoch 2548/10000, Train Loss: 1.3664, Train Accuracy: 0.5703, Val Loss: 1.3882, Val Accuracy: 0.5179
Epoch 2549/10000, Train Loss: 1.3699, Train Accuracy: 0.5859, Val Loss: 1.3881, Val Accuracy: 0.5179
Epoch 2550/10000, Train Loss: 1.3634, Train Accuracy: 0.5804, Val Loss: 1.3880, Val Accuracy: 0.5179
Epoch 2551/10000, Train Loss: 1.3573, Train Accuracy: 0.6004, Val Loss: 1.3879, Val Accuracy: 0.5179
Epoch 2552/10000, Train Loss: 1.3681, Train Accuracy: 0.5681, Val Loss: 1.3878, Val Accuracy: 0.5179
Epoch 2553/10000, Train Loss: 1.3615, Train Accuracy: 0.5804, Val Loss: 1.3877, Val Accuracy: 0.5179
Epoch 2554/10000, Train Loss: 1.3609, Train Accuracy: 0.5781, Val Loss: 1.3876, Val Accuracy: 0.5179
Epoch 2555/10000, Train Loss: 1.3589, Train Accuracy: 0.5871, Val Loss: 1.3874, Val Accuracy: 0.5179
Epoch 2556/10000, Train Loss: 1.3642, Train Accuracy: 0.5737, Val Loss: 1.3873, Val Accuracy: 0.5179
Epoch 2557/10000, Train Loss: 1.3626, Train Accuracy: 0.5915, Val Loss: 1.3872, Val Accuracy: 0.5179
Epoch 2558/10000, Train Loss: 1.3569, Train Accuracy: 0.5837, Val Loss: 1.3872, Val Accuracy: 0.5179
Epoch 2559/10000, Train Loss: 1.3670, Train Accuracy: 0.5725, Val Loss: 1.3871, Val Accuracy: 0.5179
Epoch 2560/10000, Train Loss: 1.3644, Train Accuracy: 0.5725, Val Loss: 1.3870, Val Accuracy: 0.5179
Epoch 2561/10000, Train Loss: 1.3669, Train Accuracy: 0.5658, Val Loss: 1.3869, Val Accuracy: 0.5179
Epoch 2562/10000, Train Loss: 1.3706, Train Accuracy: 0.5658, Val Loss: 1.3868, Val Accuracy: 0.5179
Epoch 2563/10000, Train Loss: 1.3584, Train Accuracy: 0.5748, Val Loss: 1.3867, Val Accuracy: 0.5179
Epoch 2564/10000, Train Loss: 1.3643, Train Accuracy: 0.5703, Val Loss: 1.3866, Val Accuracy: 0.5179
Epoch 2565/10000, Train Loss: 1.3573, Train Accuracy: 0.5971, Val Loss: 1.3865, Val Accuracy: 0.5179
Epoch 2566/10000, Train Loss: 1.3596, Train Accuracy: 0.5882, Val Loss: 1.3864, Val Accuracy: 0.5179
Epoch 2567/10000, Train Loss: 1.3695, Train Accuracy: 0.5670, Val Loss: 1.3863, Val Accuracy: 0.5179
Epoch 2568/10000, Train Loss: 1.3635, Train Accuracy: 0.5703, Val Loss: 1.3862, Val Accuracy: 0.5179
Epoch 2569/10000, Train Loss: 1.3706, Train Accuracy: 0.5737, Val Loss: 1.3861, Val Accuracy: 0.5179
Epoch 2570/10000, Train Loss: 1.3656, Train Accuracy: 0.5737, Val Loss: 1.3860, Val Accuracy: 0.5179
Epoch 2571/10000, Train Loss: 1.3664, Train Accuracy: 0.5770, Val Loss: 1.3859, Val Accuracy: 0.5179
Epoch 2572/10000, Train Loss: 1.3566, Train Accuracy: 0.5725, Val Loss: 1.3858, Val Accuracy: 0.5179
Epoch 2573/10000, Train Loss: 1.3574, Train Accuracy: 0.5938, Val Loss: 1.3857, Val Accuracy: 0.5179
Epoch 2574/10000, Train Loss: 1.3691, Train Accuracy: 0.5714, Val Loss: 1.3855, Val Accuracy: 0.5179
Epoch 2575/10000, Train Loss: 1.3552, Train Accuracy: 0.5982, Val Loss: 1.3854, Val Accuracy: 0.5179
Epoch 2576/10000, Train Loss: 1.3640, Train Accuracy: 0.5938, Val Loss: 1.3853, Val Accuracy: 0.5179
Epoch 2577/10000, Train Loss: 1.3527, Train Accuracy: 0.5882, Val Loss: 1.3852, Val Accuracy: 0.5179
Epoch 2578/10000, Train Loss: 1.3667, Train Accuracy: 0.5882, Val Loss: 1.3851, Val Accuracy: 0.5179
Epoch 2579/10000, Train Loss: 1.3649, Train Accuracy: 0.5837, Val Loss: 1.3850, Val Accuracy: 0.5179
Epoch 2580/10000, Train Loss: 1.3553, Train Accuracy: 0.5904, Val Loss: 1.3849, Val Accuracy: 0.5179
Epoch 2581/10000, Train Loss: 1.3616, Train Accuracy: 0.5670, Val Loss: 1.3847, Val Accuracy: 0.5134
Epoch 2582/10000, Train Loss: 1.3624, Train Accuracy: 0.5871, Val Loss: 1.3846, Val Accuracy: 0.5134
Epoch 2583/10000, Train Loss: 1.3613, Train Accuracy: 0.5904, Val Loss: 1.3846, Val Accuracy: 0.5134
Epoch 2584/10000, Train Loss: 1.3602, Train Accuracy: 0.5837, Val Loss: 1.3845, Val Accuracy: 0.5134
Epoch 2585/10000, Train Loss: 1.3630, Train Accuracy: 0.5815, Val Loss: 1.3844, Val Accuracy: 0.5134
Epoch 2586/10000, Train Loss: 1.3682, Train Accuracy: 0.5592, Val Loss: 1.3843, Val Accuracy: 0.5134
Epoch 2587/10000, Train Loss: 1.3601, Train Accuracy: 0.5792, Val Loss: 1.3843, Val Accuracy: 0.5134
Epoch 2588/10000, Train Loss: 1.3631, Train Accuracy: 0.5737, Val Loss: 1.3841, Val Accuracy: 0.5179
Epoch 2589/10000, Train Loss: 1.3635, Train Accuracy: 0.5837, Val Loss: 1.3841, Val Accuracy: 0.5179
Epoch 2590/10000, Train Loss: 1.3580, Train Accuracy: 0.5781, Val Loss: 1.3840, Val Accuracy: 0.5179
Epoch 2591/10000, Train Loss: 1.3626, Train Accuracy: 0.5859, Val Loss: 1.3839, Val Accuracy: 0.5134
Epoch 2592/10000, Train Loss: 1.3597, Train Accuracy: 0.5737, Val Loss: 1.3839, Val Accuracy: 0.5134
Epoch 2593/10000, Train Loss: 1.3523, Train Accuracy: 0.5926, Val Loss: 1.3838, Val Accuracy: 0.5134
Epoch 2594/10000, Train Loss: 1.3542, Train Accuracy: 0.6150, Val Loss: 1.3836, Val Accuracy: 0.5134
Epoch 2595/10000, Train Loss: 1.3561, Train Accuracy: 0.5893, Val Loss: 1.3836, Val Accuracy: 0.5134
Epoch 2596/10000, Train Loss: 1.3690, Train Accuracy: 0.5647, Val Loss: 1.3835, Val Accuracy: 0.5134
Epoch 2597/10000, Train Loss: 1.3548, Train Accuracy: 0.6027, Val Loss: 1.3834, Val Accuracy: 0.5134
Epoch 2598/10000, Train Loss: 1.3643, Train Accuracy: 0.5915, Val Loss: 1.3833, Val Accuracy: 0.5134
Epoch 2599/10000, Train Loss: 1.3630, Train Accuracy: 0.5859, Val Loss: 1.3832, Val Accuracy: 0.5134
Epoch 2600/10000, Train Loss: 1.3581, Train Accuracy: 0.5848, Val Loss: 1.3832, Val Accuracy: 0.5134
Epoch 2601/10000, Train Loss: 1.3524, Train Accuracy: 0.5982, Val Loss: 1.3830, Val Accuracy: 0.5134
Epoch 2602/10000, Train Loss: 1.3503, Train Accuracy: 0.5893, Val Loss: 1.3829, Val Accuracy: 0.5134
Epoch 2603/10000, Train Loss: 1.3536, Train Accuracy: 0.5837, Val Loss: 1.3828, Val Accuracy: 0.5134
Epoch 2604/10000, Train Loss: 1.3596, Train Accuracy: 0.5859, Val Loss: 1.3827, Val Accuracy: 0.5134
Epoch 2605/10000, Train Loss: 1.3504, Train Accuracy: 0.5960, Val Loss: 1.3825, Val Accuracy: 0.5179
Epoch 2606/10000, Train Loss: 1.3562, Train Accuracy: 0.5837, Val Loss: 1.3825, Val Accuracy: 0.5179
Epoch 2607/10000, Train Loss: 1.3613, Train Accuracy: 0.5725, Val Loss: 1.3824, Val Accuracy: 0.5134
Epoch 2608/10000, Train Loss: 1.3595, Train Accuracy: 0.5603, Val Loss: 1.3823, Val Accuracy: 0.5134
Epoch 2609/10000, Train Loss: 1.3534, Train Accuracy: 0.5893, Val Loss: 1.3822, Val Accuracy: 0.5134
Epoch 2610/10000, Train Loss: 1.3645, Train Accuracy: 0.5781, Val Loss: 1.3821, Val Accuracy: 0.5134
Epoch 2611/10000, Train Loss: 1.3584, Train Accuracy: 0.5837, Val Loss: 1.3820, Val Accuracy: 0.5134
Epoch 2612/10000, Train Loss: 1.3619, Train Accuracy: 0.5770, Val Loss: 1.3819, Val Accuracy: 0.5134
Epoch 2613/10000, Train Loss: 1.3619, Train Accuracy: 0.5770, Val Loss: 1.3818, Val Accuracy: 0.5134
Epoch 2614/10000, Train Loss: 1.3613, Train Accuracy: 0.5770, Val Loss: 1.3818, Val Accuracy: 0.5134
Epoch 2615/10000, Train Loss: 1.3616, Train Accuracy: 0.5692, Val Loss: 1.3817, Val Accuracy: 0.5179
Epoch 2616/10000, Train Loss: 1.3562, Train Accuracy: 0.5681, Val Loss: 1.3816, Val Accuracy: 0.5134
Epoch 2617/10000, Train Loss: 1.3558, Train Accuracy: 0.5848, Val Loss: 1.3815, Val Accuracy: 0.5179
Epoch 2618/10000, Train Loss: 1.3540, Train Accuracy: 0.5871, Val Loss: 1.3815, Val Accuracy: 0.5179
Epoch 2619/10000, Train Loss: 1.3574, Train Accuracy: 0.5926, Val Loss: 1.3814, Val Accuracy: 0.5134
Epoch 2620/10000, Train Loss: 1.3571, Train Accuracy: 0.5759, Val Loss: 1.3813, Val Accuracy: 0.5179
Epoch 2621/10000, Train Loss: 1.3562, Train Accuracy: 0.5781, Val Loss: 1.3813, Val Accuracy: 0.5134
Epoch 2622/10000, Train Loss: 1.3525, Train Accuracy: 0.5960, Val Loss: 1.3812, Val Accuracy: 0.5134
Epoch 2623/10000, Train Loss: 1.3595, Train Accuracy: 0.5725, Val Loss: 1.3811, Val Accuracy: 0.5179
Epoch 2624/10000, Train Loss: 1.3562, Train Accuracy: 0.5949, Val Loss: 1.3810, Val Accuracy: 0.5179
Epoch 2625/10000, Train Loss: 1.3620, Train Accuracy: 0.5725, Val Loss: 1.3809, Val Accuracy: 0.5179
Epoch 2626/10000, Train Loss: 1.3595, Train Accuracy: 0.5893, Val Loss: 1.3808, Val Accuracy: 0.5179
Epoch 2627/10000, Train Loss: 1.3513, Train Accuracy: 0.5915, Val Loss: 1.3807, Val Accuracy: 0.5179
Epoch 2628/10000, Train Loss: 1.3530, Train Accuracy: 0.5848, Val Loss: 1.3806, Val Accuracy: 0.5179
Epoch 2629/10000, Train Loss: 1.3650, Train Accuracy: 0.5737, Val Loss: 1.3805, Val Accuracy: 0.5179
Epoch 2630/10000, Train Loss: 1.3494, Train Accuracy: 0.5893, Val Loss: 1.3804, Val Accuracy: 0.5179
Epoch 2631/10000, Train Loss: 1.3626, Train Accuracy: 0.5636, Val Loss: 1.3803, Val Accuracy: 0.5179
Epoch 2632/10000, Train Loss: 1.3436, Train Accuracy: 0.6071, Val Loss: 1.3802, Val Accuracy: 0.5179
Epoch 2633/10000, Train Loss: 1.3576, Train Accuracy: 0.5636, Val Loss: 1.3802, Val Accuracy: 0.5179
Epoch 2634/10000, Train Loss: 1.3588, Train Accuracy: 0.5882, Val Loss: 1.3801, Val Accuracy: 0.5179
Epoch 2635/10000, Train Loss: 1.3534, Train Accuracy: 0.5926, Val Loss: 1.3800, Val Accuracy: 0.5179
Epoch 2636/10000, Train Loss: 1.3578, Train Accuracy: 0.5882, Val Loss: 1.3799, Val Accuracy: 0.5179
Epoch 2637/10000, Train Loss: 1.3545, Train Accuracy: 0.5859, Val Loss: 1.3798, Val Accuracy: 0.5179
Epoch 2638/10000, Train Loss: 1.3537, Train Accuracy: 0.5859, Val Loss: 1.3797, Val Accuracy: 0.5179
Epoch 2639/10000, Train Loss: 1.3549, Train Accuracy: 0.5926, Val Loss: 1.3796, Val Accuracy: 0.5179
Epoch 2640/10000, Train Loss: 1.3537, Train Accuracy: 0.5960, Val Loss: 1.3796, Val Accuracy: 0.5179
Epoch 2641/10000, Train Loss: 1.3538, Train Accuracy: 0.5871, Val Loss: 1.3795, Val Accuracy: 0.5223
Epoch 2642/10000, Train Loss: 1.3611, Train Accuracy: 0.5759, Val Loss: 1.3794, Val Accuracy: 0.5223
Epoch 2643/10000, Train Loss: 1.3529, Train Accuracy: 0.5859, Val Loss: 1.3793, Val Accuracy: 0.5223
Epoch 2644/10000, Train Loss: 1.3529, Train Accuracy: 0.5848, Val Loss: 1.3792, Val Accuracy: 0.5223
Epoch 2645/10000, Train Loss: 1.3504, Train Accuracy: 0.5859, Val Loss: 1.3791, Val Accuracy: 0.5223
Epoch 2646/10000, Train Loss: 1.3515, Train Accuracy: 0.5871, Val Loss: 1.3790, Val Accuracy: 0.5179
Epoch 2647/10000, Train Loss: 1.3544, Train Accuracy: 0.5893, Val Loss: 1.3789, Val Accuracy: 0.5179
Epoch 2648/10000, Train Loss: 1.3592, Train Accuracy: 0.5826, Val Loss: 1.3789, Val Accuracy: 0.5223
Epoch 2649/10000, Train Loss: 1.3576, Train Accuracy: 0.5703, Val Loss: 1.3788, Val Accuracy: 0.5223
Epoch 2650/10000, Train Loss: 1.3569, Train Accuracy: 0.5714, Val Loss: 1.3787, Val Accuracy: 0.5223
Epoch 2651/10000, Train Loss: 1.3524, Train Accuracy: 0.5826, Val Loss: 1.3786, Val Accuracy: 0.5223
Epoch 2652/10000, Train Loss: 1.3569, Train Accuracy: 0.5804, Val Loss: 1.3785, Val Accuracy: 0.5223
Epoch 2653/10000, Train Loss: 1.3457, Train Accuracy: 0.5815, Val Loss: 1.3783, Val Accuracy: 0.5223
Epoch 2654/10000, Train Loss: 1.3492, Train Accuracy: 0.6004, Val Loss: 1.3783, Val Accuracy: 0.5223
Epoch 2655/10000, Train Loss: 1.3545, Train Accuracy: 0.5871, Val Loss: 1.3782, Val Accuracy: 0.5223
Epoch 2656/10000, Train Loss: 1.3456, Train Accuracy: 0.5915, Val Loss: 1.3781, Val Accuracy: 0.5223
Epoch 2657/10000, Train Loss: 1.3447, Train Accuracy: 0.5982, Val Loss: 1.3780, Val Accuracy: 0.5223
Epoch 2658/10000, Train Loss: 1.3508, Train Accuracy: 0.5804, Val Loss: 1.3780, Val Accuracy: 0.5223
Epoch 2659/10000, Train Loss: 1.3578, Train Accuracy: 0.5748, Val Loss: 1.3778, Val Accuracy: 0.5223
Epoch 2660/10000, Train Loss: 1.3571, Train Accuracy: 0.5893, Val Loss: 1.3777, Val Accuracy: 0.5223
Epoch 2661/10000, Train Loss: 1.3477, Train Accuracy: 0.5882, Val Loss: 1.3776, Val Accuracy: 0.5223
Epoch 2662/10000, Train Loss: 1.3483, Train Accuracy: 0.6038, Val Loss: 1.3775, Val Accuracy: 0.5223
Epoch 2663/10000, Train Loss: 1.3497, Train Accuracy: 0.5938, Val Loss: 1.3775, Val Accuracy: 0.5223
Epoch 2664/10000, Train Loss: 1.3519, Train Accuracy: 0.6060, Val Loss: 1.3774, Val Accuracy: 0.5223
Epoch 2665/10000, Train Loss: 1.3523, Train Accuracy: 0.5938, Val Loss: 1.3773, Val Accuracy: 0.5268
Epoch 2666/10000, Train Loss: 1.3537, Train Accuracy: 0.5837, Val Loss: 1.3772, Val Accuracy: 0.5268
Epoch 2667/10000, Train Loss: 1.3496, Train Accuracy: 0.5848, Val Loss: 1.3771, Val Accuracy: 0.5268
Epoch 2668/10000, Train Loss: 1.3444, Train Accuracy: 0.5949, Val Loss: 1.3770, Val Accuracy: 0.5268
Epoch 2669/10000, Train Loss: 1.3559, Train Accuracy: 0.5871, Val Loss: 1.3769, Val Accuracy: 0.5268
Epoch 2670/10000, Train Loss: 1.3528, Train Accuracy: 0.5882, Val Loss: 1.3768, Val Accuracy: 0.5268
Epoch 2671/10000, Train Loss: 1.3564, Train Accuracy: 0.5792, Val Loss: 1.3767, Val Accuracy: 0.5268
Epoch 2672/10000, Train Loss: 1.3484, Train Accuracy: 0.6083, Val Loss: 1.3766, Val Accuracy: 0.5268
Epoch 2673/10000, Train Loss: 1.3485, Train Accuracy: 0.5904, Val Loss: 1.3765, Val Accuracy: 0.5268
Epoch 2674/10000, Train Loss: 1.3446, Train Accuracy: 0.6071, Val Loss: 1.3764, Val Accuracy: 0.5268
Epoch 2675/10000, Train Loss: 1.3425, Train Accuracy: 0.6116, Val Loss: 1.3763, Val Accuracy: 0.5268
Epoch 2676/10000, Train Loss: 1.3519, Train Accuracy: 0.5837, Val Loss: 1.3762, Val Accuracy: 0.5268
Epoch 2677/10000, Train Loss: 1.3477, Train Accuracy: 0.6049, Val Loss: 1.3760, Val Accuracy: 0.5268
Epoch 2678/10000, Train Loss: 1.3497, Train Accuracy: 0.5647, Val Loss: 1.3760, Val Accuracy: 0.5268
Epoch 2679/10000, Train Loss: 1.3461, Train Accuracy: 0.5960, Val Loss: 1.3759, Val Accuracy: 0.5268
Epoch 2680/10000, Train Loss: 1.3531, Train Accuracy: 0.5982, Val Loss: 1.3758, Val Accuracy: 0.5268
Epoch 2681/10000, Train Loss: 1.3489, Train Accuracy: 0.5904, Val Loss: 1.3757, Val Accuracy: 0.5268
Epoch 2682/10000, Train Loss: 1.3408, Train Accuracy: 0.6038, Val Loss: 1.3757, Val Accuracy: 0.5312
Epoch 2683/10000, Train Loss: 1.3452, Train Accuracy: 0.5915, Val Loss: 1.3756, Val Accuracy: 0.5312
Epoch 2684/10000, Train Loss: 1.3526, Train Accuracy: 0.5759, Val Loss: 1.3756, Val Accuracy: 0.5312
Epoch 2685/10000, Train Loss: 1.3465, Train Accuracy: 0.5971, Val Loss: 1.3754, Val Accuracy: 0.5312
Epoch 2686/10000, Train Loss: 1.3467, Train Accuracy: 0.6049, Val Loss: 1.3753, Val Accuracy: 0.5312
Epoch 2687/10000, Train Loss: 1.3543, Train Accuracy: 0.5681, Val Loss: 1.3752, Val Accuracy: 0.5312
Epoch 2688/10000, Train Loss: 1.3454, Train Accuracy: 0.5949, Val Loss: 1.3750, Val Accuracy: 0.5312
Epoch 2689/10000, Train Loss: 1.3463, Train Accuracy: 0.5982, Val Loss: 1.3749, Val Accuracy: 0.5312
Epoch 2690/10000, Train Loss: 1.3451, Train Accuracy: 0.5904, Val Loss: 1.3748, Val Accuracy: 0.5312
Epoch 2691/10000, Train Loss: 1.3470, Train Accuracy: 0.5949, Val Loss: 1.3747, Val Accuracy: 0.5312
Epoch 2692/10000, Train Loss: 1.3478, Train Accuracy: 0.5915, Val Loss: 1.3747, Val Accuracy: 0.5312
Epoch 2693/10000, Train Loss: 1.3552, Train Accuracy: 0.5737, Val Loss: 1.3746, Val Accuracy: 0.5312
Epoch 2694/10000, Train Loss: 1.3440, Train Accuracy: 0.5993, Val Loss: 1.3745, Val Accuracy: 0.5312
Epoch 2695/10000, Train Loss: 1.3464, Train Accuracy: 0.5893, Val Loss: 1.3744, Val Accuracy: 0.5312
Epoch 2696/10000, Train Loss: 1.3474, Train Accuracy: 0.5971, Val Loss: 1.3743, Val Accuracy: 0.5312
Epoch 2697/10000, Train Loss: 1.3541, Train Accuracy: 0.5859, Val Loss: 1.3743, Val Accuracy: 0.5312
Epoch 2698/10000, Train Loss: 1.3445, Train Accuracy: 0.5938, Val Loss: 1.3742, Val Accuracy: 0.5312
Epoch 2699/10000, Train Loss: 1.3469, Train Accuracy: 0.5893, Val Loss: 1.3741, Val Accuracy: 0.5312
Epoch 2700/10000, Train Loss: 1.3365, Train Accuracy: 0.6094, Val Loss: 1.3740, Val Accuracy: 0.5312
Epoch 2701/10000, Train Loss: 1.3439, Train Accuracy: 0.5926, Val Loss: 1.3739, Val Accuracy: 0.5312
Epoch 2702/10000, Train Loss: 1.3539, Train Accuracy: 0.5792, Val Loss: 1.3738, Val Accuracy: 0.5312
Epoch 2703/10000, Train Loss: 1.3476, Train Accuracy: 0.5804, Val Loss: 1.3737, Val Accuracy: 0.5312
Epoch 2704/10000, Train Loss: 1.3505, Train Accuracy: 0.5859, Val Loss: 1.3736, Val Accuracy: 0.5312
Epoch 2705/10000, Train Loss: 1.3487, Train Accuracy: 0.5915, Val Loss: 1.3735, Val Accuracy: 0.5312
Epoch 2706/10000, Train Loss: 1.3469, Train Accuracy: 0.5960, Val Loss: 1.3734, Val Accuracy: 0.5312
Epoch 2707/10000, Train Loss: 1.3474, Train Accuracy: 0.5882, Val Loss: 1.3733, Val Accuracy: 0.5312
Epoch 2708/10000, Train Loss: 1.3486, Train Accuracy: 0.5915, Val Loss: 1.3732, Val Accuracy: 0.5312
Epoch 2709/10000, Train Loss: 1.3427, Train Accuracy: 0.6004, Val Loss: 1.3732, Val Accuracy: 0.5312
Epoch 2710/10000, Train Loss: 1.3388, Train Accuracy: 0.6094, Val Loss: 1.3731, Val Accuracy: 0.5312
Epoch 2711/10000, Train Loss: 1.3429, Train Accuracy: 0.5915, Val Loss: 1.3730, Val Accuracy: 0.5312
Epoch 2712/10000, Train Loss: 1.3586, Train Accuracy: 0.5837, Val Loss: 1.3729, Val Accuracy: 0.5312
Epoch 2713/10000, Train Loss: 1.3479, Train Accuracy: 0.5926, Val Loss: 1.3728, Val Accuracy: 0.5312
Epoch 2714/10000, Train Loss: 1.3365, Train Accuracy: 0.6116, Val Loss: 1.3727, Val Accuracy: 0.5312
Epoch 2715/10000, Train Loss: 1.3536, Train Accuracy: 0.5804, Val Loss: 1.3726, Val Accuracy: 0.5312
Epoch 2716/10000, Train Loss: 1.3428, Train Accuracy: 0.6071, Val Loss: 1.3725, Val Accuracy: 0.5312
Epoch 2717/10000, Train Loss: 1.3379, Train Accuracy: 0.6071, Val Loss: 1.3724, Val Accuracy: 0.5312
Epoch 2718/10000, Train Loss: 1.3446, Train Accuracy: 0.5915, Val Loss: 1.3723, Val Accuracy: 0.5268
Epoch 2719/10000, Train Loss: 1.3515, Train Accuracy: 0.5804, Val Loss: 1.3722, Val Accuracy: 0.5268
Epoch 2720/10000, Train Loss: 1.3452, Train Accuracy: 0.5949, Val Loss: 1.3722, Val Accuracy: 0.5223
Epoch 2721/10000, Train Loss: 1.3357, Train Accuracy: 0.6194, Val Loss: 1.3721, Val Accuracy: 0.5223
Epoch 2722/10000, Train Loss: 1.3433, Train Accuracy: 0.5938, Val Loss: 1.3720, Val Accuracy: 0.5223
Epoch 2723/10000, Train Loss: 1.3516, Train Accuracy: 0.5926, Val Loss: 1.3719, Val Accuracy: 0.5268
Epoch 2724/10000, Train Loss: 1.3496, Train Accuracy: 0.5915, Val Loss: 1.3718, Val Accuracy: 0.5223
Epoch 2725/10000, Train Loss: 1.3452, Train Accuracy: 0.5871, Val Loss: 1.3717, Val Accuracy: 0.5268
Epoch 2726/10000, Train Loss: 1.3445, Train Accuracy: 0.6038, Val Loss: 1.3716, Val Accuracy: 0.5223
Epoch 2727/10000, Train Loss: 1.3364, Train Accuracy: 0.6194, Val Loss: 1.3715, Val Accuracy: 0.5312
Epoch 2728/10000, Train Loss: 1.3348, Train Accuracy: 0.6116, Val Loss: 1.3714, Val Accuracy: 0.5223
Epoch 2729/10000, Train Loss: 1.3410, Train Accuracy: 0.6027, Val Loss: 1.3713, Val Accuracy: 0.5179
Epoch 2730/10000, Train Loss: 1.3355, Train Accuracy: 0.6038, Val Loss: 1.3713, Val Accuracy: 0.5179
Epoch 2731/10000, Train Loss: 1.3395, Train Accuracy: 0.6116, Val Loss: 1.3712, Val Accuracy: 0.5223
Epoch 2732/10000, Train Loss: 1.3495, Train Accuracy: 0.5759, Val Loss: 1.3712, Val Accuracy: 0.5223
Epoch 2733/10000, Train Loss: 1.3377, Train Accuracy: 0.6060, Val Loss: 1.3711, Val Accuracy: 0.5223
Epoch 2734/10000, Train Loss: 1.3369, Train Accuracy: 0.5938, Val Loss: 1.3710, Val Accuracy: 0.5223
Epoch 2735/10000, Train Loss: 1.3406, Train Accuracy: 0.6060, Val Loss: 1.3709, Val Accuracy: 0.5268
Epoch 2736/10000, Train Loss: 1.3448, Train Accuracy: 0.5837, Val Loss: 1.3708, Val Accuracy: 0.5268
Epoch 2737/10000, Train Loss: 1.3415, Train Accuracy: 0.5893, Val Loss: 1.3707, Val Accuracy: 0.5268
Epoch 2738/10000, Train Loss: 1.3414, Train Accuracy: 0.5993, Val Loss: 1.3706, Val Accuracy: 0.5268
Epoch 2739/10000, Train Loss: 1.3384, Train Accuracy: 0.6094, Val Loss: 1.3706, Val Accuracy: 0.5268
Epoch 2740/10000, Train Loss: 1.3430, Train Accuracy: 0.5815, Val Loss: 1.3705, Val Accuracy: 0.5268
Epoch 2741/10000, Train Loss: 1.3509, Train Accuracy: 0.5848, Val Loss: 1.3704, Val Accuracy: 0.5268
Epoch 2742/10000, Train Loss: 1.3459, Train Accuracy: 0.5893, Val Loss: 1.3703, Val Accuracy: 0.5268
Epoch 2743/10000, Train Loss: 1.3341, Train Accuracy: 0.6094, Val Loss: 1.3702, Val Accuracy: 0.5268
Epoch 2744/10000, Train Loss: 1.3419, Train Accuracy: 0.6027, Val Loss: 1.3701, Val Accuracy: 0.5268
Epoch 2745/10000, Train Loss: 1.3436, Train Accuracy: 0.5915, Val Loss: 1.3700, Val Accuracy: 0.5268
Epoch 2746/10000, Train Loss: 1.3418, Train Accuracy: 0.5938, Val Loss: 1.3699, Val Accuracy: 0.5268
Epoch 2747/10000, Train Loss: 1.3436, Train Accuracy: 0.5859, Val Loss: 1.3699, Val Accuracy: 0.5268
Epoch 2748/10000, Train Loss: 1.3446, Train Accuracy: 0.5960, Val Loss: 1.3698, Val Accuracy: 0.5268
Epoch 2749/10000, Train Loss: 1.3476, Train Accuracy: 0.5848, Val Loss: 1.3696, Val Accuracy: 0.5268
Epoch 2750/10000, Train Loss: 1.3453, Train Accuracy: 0.5949, Val Loss: 1.3695, Val Accuracy: 0.5268
Epoch 2751/10000, Train Loss: 1.3396, Train Accuracy: 0.6004, Val Loss: 1.3695, Val Accuracy: 0.5268
Epoch 2752/10000, Train Loss: 1.3347, Train Accuracy: 0.6150, Val Loss: 1.3694, Val Accuracy: 0.5268
Epoch 2753/10000, Train Loss: 1.3431, Train Accuracy: 0.5993, Val Loss: 1.3694, Val Accuracy: 0.5268
Epoch 2754/10000, Train Loss: 1.3389, Train Accuracy: 0.5971, Val Loss: 1.3693, Val Accuracy: 0.5268
Epoch 2755/10000, Train Loss: 1.3422, Train Accuracy: 0.5893, Val Loss: 1.3692, Val Accuracy: 0.5268
Epoch 2756/10000, Train Loss: 1.3380, Train Accuracy: 0.5960, Val Loss: 1.3691, Val Accuracy: 0.5268
Epoch 2757/10000, Train Loss: 1.3389, Train Accuracy: 0.6060, Val Loss: 1.3690, Val Accuracy: 0.5268
Epoch 2758/10000, Train Loss: 1.3318, Train Accuracy: 0.6161, Val Loss: 1.3689, Val Accuracy: 0.5268
Epoch 2759/10000, Train Loss: 1.3425, Train Accuracy: 0.6060, Val Loss: 1.3688, Val Accuracy: 0.5268
Epoch 2760/10000, Train Loss: 1.3369, Train Accuracy: 0.6016, Val Loss: 1.3687, Val Accuracy: 0.5268
Epoch 2761/10000, Train Loss: 1.3412, Train Accuracy: 0.6016, Val Loss: 1.3686, Val Accuracy: 0.5268
Epoch 2762/10000, Train Loss: 1.3424, Train Accuracy: 0.6004, Val Loss: 1.3685, Val Accuracy: 0.5268
Epoch 2763/10000, Train Loss: 1.3449, Train Accuracy: 0.5837, Val Loss: 1.3684, Val Accuracy: 0.5268
Epoch 2764/10000, Train Loss: 1.3357, Train Accuracy: 0.6116, Val Loss: 1.3683, Val Accuracy: 0.5268
Epoch 2765/10000, Train Loss: 1.3302, Train Accuracy: 0.6105, Val Loss: 1.3682, Val Accuracy: 0.5268
Epoch 2766/10000, Train Loss: 1.3402, Train Accuracy: 0.5949, Val Loss: 1.3681, Val Accuracy: 0.5268
Epoch 2767/10000, Train Loss: 1.3362, Train Accuracy: 0.5926, Val Loss: 1.3680, Val Accuracy: 0.5268
Epoch 2768/10000, Train Loss: 1.3450, Train Accuracy: 0.5871, Val Loss: 1.3679, Val Accuracy: 0.5268
Epoch 2769/10000, Train Loss: 1.3455, Train Accuracy: 0.5748, Val Loss: 1.3678, Val Accuracy: 0.5268
Epoch 2770/10000, Train Loss: 1.3420, Train Accuracy: 0.5915, Val Loss: 1.3677, Val Accuracy: 0.5268
Epoch 2771/10000, Train Loss: 1.3351, Train Accuracy: 0.6083, Val Loss: 1.3677, Val Accuracy: 0.5268
Epoch 2772/10000, Train Loss: 1.3408, Train Accuracy: 0.6038, Val Loss: 1.3676, Val Accuracy: 0.5268
Epoch 2773/10000, Train Loss: 1.3335, Train Accuracy: 0.6127, Val Loss: 1.3675, Val Accuracy: 0.5268
Epoch 2774/10000, Train Loss: 1.3378, Train Accuracy: 0.5960, Val Loss: 1.3674, Val Accuracy: 0.5268
Epoch 2775/10000, Train Loss: 1.3371, Train Accuracy: 0.6127, Val Loss: 1.3673, Val Accuracy: 0.5268
Epoch 2776/10000, Train Loss: 1.3431, Train Accuracy: 0.6016, Val Loss: 1.3673, Val Accuracy: 0.5268
Epoch 2777/10000, Train Loss: 1.3415, Train Accuracy: 0.5971, Val Loss: 1.3672, Val Accuracy: 0.5268
Epoch 2778/10000, Train Loss: 1.3359, Train Accuracy: 0.6060, Val Loss: 1.3671, Val Accuracy: 0.5268
Epoch 2779/10000, Train Loss: 1.3488, Train Accuracy: 0.5770, Val Loss: 1.3670, Val Accuracy: 0.5268
Epoch 2780/10000, Train Loss: 1.3273, Train Accuracy: 0.6071, Val Loss: 1.3669, Val Accuracy: 0.5268
Epoch 2781/10000, Train Loss: 1.3322, Train Accuracy: 0.6116, Val Loss: 1.3668, Val Accuracy: 0.5268
Epoch 2782/10000, Train Loss: 1.3351, Train Accuracy: 0.5993, Val Loss: 1.3668, Val Accuracy: 0.5268
Epoch 2783/10000, Train Loss: 1.3357, Train Accuracy: 0.6105, Val Loss: 1.3667, Val Accuracy: 0.5268
Epoch 2784/10000, Train Loss: 1.3335, Train Accuracy: 0.6060, Val Loss: 1.3666, Val Accuracy: 0.5312
Epoch 2785/10000, Train Loss: 1.3449, Train Accuracy: 0.5893, Val Loss: 1.3665, Val Accuracy: 0.5268
Epoch 2786/10000, Train Loss: 1.3360, Train Accuracy: 0.6161, Val Loss: 1.3664, Val Accuracy: 0.5268
Epoch 2787/10000, Train Loss: 1.3359, Train Accuracy: 0.6049, Val Loss: 1.3664, Val Accuracy: 0.5268
Epoch 2788/10000, Train Loss: 1.3440, Train Accuracy: 0.5804, Val Loss: 1.3663, Val Accuracy: 0.5268
Epoch 2789/10000, Train Loss: 1.3456, Train Accuracy: 0.5971, Val Loss: 1.3663, Val Accuracy: 0.5312
Epoch 2790/10000, Train Loss: 1.3397, Train Accuracy: 0.5915, Val Loss: 1.3662, Val Accuracy: 0.5312
Epoch 2791/10000, Train Loss: 1.3316, Train Accuracy: 0.6150, Val Loss: 1.3661, Val Accuracy: 0.5312
Epoch 2792/10000, Train Loss: 1.3353, Train Accuracy: 0.5949, Val Loss: 1.3660, Val Accuracy: 0.5312
Epoch 2793/10000, Train Loss: 1.3334, Train Accuracy: 0.5971, Val Loss: 1.3659, Val Accuracy: 0.5312
Epoch 2794/10000, Train Loss: 1.3249, Train Accuracy: 0.6194, Val Loss: 1.3658, Val Accuracy: 0.5312
Epoch 2795/10000, Train Loss: 1.3346, Train Accuracy: 0.5982, Val Loss: 1.3657, Val Accuracy: 0.5312
Epoch 2796/10000, Train Loss: 1.3344, Train Accuracy: 0.6049, Val Loss: 1.3657, Val Accuracy: 0.5312
Epoch 2797/10000, Train Loss: 1.3421, Train Accuracy: 0.5949, Val Loss: 1.3656, Val Accuracy: 0.5312
Epoch 2798/10000, Train Loss: 1.3347, Train Accuracy: 0.6071, Val Loss: 1.3655, Val Accuracy: 0.5312
Epoch 2799/10000, Train Loss: 1.3320, Train Accuracy: 0.6116, Val Loss: 1.3655, Val Accuracy: 0.5312
Epoch 2800/10000, Train Loss: 1.3380, Train Accuracy: 0.5993, Val Loss: 1.3654, Val Accuracy: 0.5312
Epoch 2801/10000, Train Loss: 1.3271, Train Accuracy: 0.6250, Val Loss: 1.3653, Val Accuracy: 0.5312
Epoch 2802/10000, Train Loss: 1.3401, Train Accuracy: 0.5926, Val Loss: 1.3652, Val Accuracy: 0.5312
Epoch 2803/10000, Train Loss: 1.3370, Train Accuracy: 0.6016, Val Loss: 1.3651, Val Accuracy: 0.5312
Epoch 2804/10000, Train Loss: 1.3326, Train Accuracy: 0.6138, Val Loss: 1.3651, Val Accuracy: 0.5312
Epoch 2805/10000, Train Loss: 1.3387, Train Accuracy: 0.5926, Val Loss: 1.3650, Val Accuracy: 0.5312
Epoch 2806/10000, Train Loss: 1.3292, Train Accuracy: 0.5871, Val Loss: 1.3649, Val Accuracy: 0.5312
Epoch 2807/10000, Train Loss: 1.3400, Train Accuracy: 0.5781, Val Loss: 1.3649, Val Accuracy: 0.5312
Epoch 2808/10000, Train Loss: 1.3359, Train Accuracy: 0.6038, Val Loss: 1.3648, Val Accuracy: 0.5312
Epoch 2809/10000, Train Loss: 1.3323, Train Accuracy: 0.6094, Val Loss: 1.3647, Val Accuracy: 0.5312
Epoch 2810/10000, Train Loss: 1.3389, Train Accuracy: 0.6116, Val Loss: 1.3646, Val Accuracy: 0.5312
Epoch 2811/10000, Train Loss: 1.3265, Train Accuracy: 0.6127, Val Loss: 1.3645, Val Accuracy: 0.5312
Epoch 2812/10000, Train Loss: 1.3338, Train Accuracy: 0.6083, Val Loss: 1.3644, Val Accuracy: 0.5312
Epoch 2813/10000, Train Loss: 1.3356, Train Accuracy: 0.6161, Val Loss: 1.3644, Val Accuracy: 0.5312
Epoch 2814/10000, Train Loss: 1.3329, Train Accuracy: 0.5960, Val Loss: 1.3643, Val Accuracy: 0.5312
Epoch 2815/10000, Train Loss: 1.3429, Train Accuracy: 0.5837, Val Loss: 1.3643, Val Accuracy: 0.5312
Epoch 2816/10000, Train Loss: 1.3291, Train Accuracy: 0.6183, Val Loss: 1.3642, Val Accuracy: 0.5312
Epoch 2817/10000, Train Loss: 1.3300, Train Accuracy: 0.6138, Val Loss: 1.3640, Val Accuracy: 0.5312
Epoch 2818/10000, Train Loss: 1.3373, Train Accuracy: 0.5904, Val Loss: 1.3639, Val Accuracy: 0.5312
Epoch 2819/10000, Train Loss: 1.3410, Train Accuracy: 0.6004, Val Loss: 1.3639, Val Accuracy: 0.5312
Epoch 2820/10000, Train Loss: 1.3378, Train Accuracy: 0.5926, Val Loss: 1.3637, Val Accuracy: 0.5312
Epoch 2821/10000, Train Loss: 1.3354, Train Accuracy: 0.5982, Val Loss: 1.3636, Val Accuracy: 0.5312
Epoch 2822/10000, Train Loss: 1.3311, Train Accuracy: 0.6094, Val Loss: 1.3635, Val Accuracy: 0.5312
Epoch 2823/10000, Train Loss: 1.3257, Train Accuracy: 0.6049, Val Loss: 1.3634, Val Accuracy: 0.5312
Epoch 2824/10000, Train Loss: 1.3313, Train Accuracy: 0.6071, Val Loss: 1.3633, Val Accuracy: 0.5312
Epoch 2825/10000, Train Loss: 1.3359, Train Accuracy: 0.5971, Val Loss: 1.3633, Val Accuracy: 0.5357
Epoch 2826/10000, Train Loss: 1.3453, Train Accuracy: 0.5915, Val Loss: 1.3632, Val Accuracy: 0.5312
Epoch 2827/10000, Train Loss: 1.3388, Train Accuracy: 0.5993, Val Loss: 1.3632, Val Accuracy: 0.5357
Epoch 2828/10000, Train Loss: 1.3324, Train Accuracy: 0.6116, Val Loss: 1.3631, Val Accuracy: 0.5357
Epoch 2829/10000, Train Loss: 1.3353, Train Accuracy: 0.6138, Val Loss: 1.3630, Val Accuracy: 0.5357
Epoch 2830/10000, Train Loss: 1.3259, Train Accuracy: 0.6228, Val Loss: 1.3629, Val Accuracy: 0.5357
Epoch 2831/10000, Train Loss: 1.3370, Train Accuracy: 0.6071, Val Loss: 1.3628, Val Accuracy: 0.5357
Epoch 2832/10000, Train Loss: 1.3359, Train Accuracy: 0.5804, Val Loss: 1.3627, Val Accuracy: 0.5357
Epoch 2833/10000, Train Loss: 1.3275, Train Accuracy: 0.6116, Val Loss: 1.3626, Val Accuracy: 0.5357
Epoch 2834/10000, Train Loss: 1.3307, Train Accuracy: 0.5993, Val Loss: 1.3626, Val Accuracy: 0.5357
Epoch 2835/10000, Train Loss: 1.3354, Train Accuracy: 0.6038, Val Loss: 1.3625, Val Accuracy: 0.5357
Epoch 2836/10000, Train Loss: 1.3290, Train Accuracy: 0.6027, Val Loss: 1.3624, Val Accuracy: 0.5357
Epoch 2837/10000, Train Loss: 1.3313, Train Accuracy: 0.5982, Val Loss: 1.3624, Val Accuracy: 0.5357
Epoch 2838/10000, Train Loss: 1.3347, Train Accuracy: 0.5893, Val Loss: 1.3623, Val Accuracy: 0.5402
Epoch 2839/10000, Train Loss: 1.3334, Train Accuracy: 0.6049, Val Loss: 1.3622, Val Accuracy: 0.5402
Epoch 2840/10000, Train Loss: 1.3314, Train Accuracy: 0.5949, Val Loss: 1.3622, Val Accuracy: 0.5402
Epoch 2841/10000, Train Loss: 1.3329, Train Accuracy: 0.5982, Val Loss: 1.3620, Val Accuracy: 0.5402
Epoch 2842/10000, Train Loss: 1.3326, Train Accuracy: 0.6116, Val Loss: 1.3620, Val Accuracy: 0.5402
Epoch 2843/10000, Train Loss: 1.3308, Train Accuracy: 0.5993, Val Loss: 1.3619, Val Accuracy: 0.5402
Epoch 2844/10000, Train Loss: 1.3452, Train Accuracy: 0.5826, Val Loss: 1.3618, Val Accuracy: 0.5402
Epoch 2845/10000, Train Loss: 1.3308, Train Accuracy: 0.6105, Val Loss: 1.3617, Val Accuracy: 0.5402
Epoch 2846/10000, Train Loss: 1.3276, Train Accuracy: 0.6060, Val Loss: 1.3616, Val Accuracy: 0.5402
Epoch 2847/10000, Train Loss: 1.3298, Train Accuracy: 0.6116, Val Loss: 1.3616, Val Accuracy: 0.5402
Epoch 2848/10000, Train Loss: 1.3242, Train Accuracy: 0.6071, Val Loss: 1.3615, Val Accuracy: 0.5402
Epoch 2849/10000, Train Loss: 1.3231, Train Accuracy: 0.6060, Val Loss: 1.3614, Val Accuracy: 0.5402
Epoch 2850/10000, Train Loss: 1.3345, Train Accuracy: 0.6027, Val Loss: 1.3613, Val Accuracy: 0.5402
Epoch 2851/10000, Train Loss: 1.3352, Train Accuracy: 0.5971, Val Loss: 1.3612, Val Accuracy: 0.5402
Epoch 2852/10000, Train Loss: 1.3323, Train Accuracy: 0.5938, Val Loss: 1.3611, Val Accuracy: 0.5402
Epoch 2853/10000, Train Loss: 1.3304, Train Accuracy: 0.6016, Val Loss: 1.3610, Val Accuracy: 0.5402
Epoch 2854/10000, Train Loss: 1.3243, Train Accuracy: 0.5971, Val Loss: 1.3609, Val Accuracy: 0.5402
Epoch 2855/10000, Train Loss: 1.3228, Train Accuracy: 0.6194, Val Loss: 1.3608, Val Accuracy: 0.5402
Epoch 2856/10000, Train Loss: 1.3394, Train Accuracy: 0.5859, Val Loss: 1.3608, Val Accuracy: 0.5402
Epoch 2857/10000, Train Loss: 1.3300, Train Accuracy: 0.6094, Val Loss: 1.3607, Val Accuracy: 0.5402
Epoch 2858/10000, Train Loss: 1.3349, Train Accuracy: 0.6038, Val Loss: 1.3606, Val Accuracy: 0.5402
Epoch 2859/10000, Train Loss: 1.3377, Train Accuracy: 0.5848, Val Loss: 1.3606, Val Accuracy: 0.5402
Epoch 2860/10000, Train Loss: 1.3239, Train Accuracy: 0.6105, Val Loss: 1.3605, Val Accuracy: 0.5402
Epoch 2861/10000, Train Loss: 1.3218, Train Accuracy: 0.6217, Val Loss: 1.3604, Val Accuracy: 0.5402
Epoch 2862/10000, Train Loss: 1.3319, Train Accuracy: 0.6205, Val Loss: 1.3603, Val Accuracy: 0.5402
Epoch 2863/10000, Train Loss: 1.3305, Train Accuracy: 0.5949, Val Loss: 1.3601, Val Accuracy: 0.5402
Epoch 2864/10000, Train Loss: 1.3285, Train Accuracy: 0.6049, Val Loss: 1.3600, Val Accuracy: 0.5402
Epoch 2865/10000, Train Loss: 1.3299, Train Accuracy: 0.6083, Val Loss: 1.3599, Val Accuracy: 0.5402
Epoch 2866/10000, Train Loss: 1.3371, Train Accuracy: 0.5993, Val Loss: 1.3598, Val Accuracy: 0.5402
Epoch 2867/10000, Train Loss: 1.3220, Train Accuracy: 0.6138, Val Loss: 1.3598, Val Accuracy: 0.5402
Epoch 2868/10000, Train Loss: 1.3261, Train Accuracy: 0.6150, Val Loss: 1.3597, Val Accuracy: 0.5402
Epoch 2869/10000, Train Loss: 1.3325, Train Accuracy: 0.5993, Val Loss: 1.3597, Val Accuracy: 0.5402
Epoch 2870/10000, Train Loss: 1.3323, Train Accuracy: 0.6105, Val Loss: 1.3595, Val Accuracy: 0.5402
Epoch 2871/10000, Train Loss: 1.3273, Train Accuracy: 0.6071, Val Loss: 1.3594, Val Accuracy: 0.5402
Epoch 2872/10000, Train Loss: 1.3175, Train Accuracy: 0.6228, Val Loss: 1.3593, Val Accuracy: 0.5402
Epoch 2873/10000, Train Loss: 1.3265, Train Accuracy: 0.6116, Val Loss: 1.3592, Val Accuracy: 0.5402
Epoch 2874/10000, Train Loss: 1.3278, Train Accuracy: 0.5993, Val Loss: 1.3591, Val Accuracy: 0.5402
Epoch 2875/10000, Train Loss: 1.3332, Train Accuracy: 0.6027, Val Loss: 1.3590, Val Accuracy: 0.5402
Epoch 2876/10000, Train Loss: 1.3270, Train Accuracy: 0.6027, Val Loss: 1.3589, Val Accuracy: 0.5402
Epoch 2877/10000, Train Loss: 1.3283, Train Accuracy: 0.6060, Val Loss: 1.3589, Val Accuracy: 0.5402
Epoch 2878/10000, Train Loss: 1.3309, Train Accuracy: 0.6060, Val Loss: 1.3588, Val Accuracy: 0.5402
Epoch 2879/10000, Train Loss: 1.3309, Train Accuracy: 0.5949, Val Loss: 1.3587, Val Accuracy: 0.5402
Epoch 2880/10000, Train Loss: 1.3264, Train Accuracy: 0.6038, Val Loss: 1.3587, Val Accuracy: 0.5402
Epoch 2881/10000, Train Loss: 1.3321, Train Accuracy: 0.5949, Val Loss: 1.3586, Val Accuracy: 0.5402
Epoch 2882/10000, Train Loss: 1.3225, Train Accuracy: 0.6138, Val Loss: 1.3585, Val Accuracy: 0.5402
Epoch 2883/10000, Train Loss: 1.3267, Train Accuracy: 0.6049, Val Loss: 1.3584, Val Accuracy: 0.5402
Epoch 2884/10000, Train Loss: 1.3270, Train Accuracy: 0.6060, Val Loss: 1.3583, Val Accuracy: 0.5402
Epoch 2885/10000, Train Loss: 1.3296, Train Accuracy: 0.5960, Val Loss: 1.3583, Val Accuracy: 0.5402
Epoch 2886/10000, Train Loss: 1.3290, Train Accuracy: 0.6094, Val Loss: 1.3581, Val Accuracy: 0.5402
Epoch 2887/10000, Train Loss: 1.3224, Train Accuracy: 0.6138, Val Loss: 1.3581, Val Accuracy: 0.5402
Epoch 2888/10000, Train Loss: 1.3230, Train Accuracy: 0.6027, Val Loss: 1.3580, Val Accuracy: 0.5402
Epoch 2889/10000, Train Loss: 1.3212, Train Accuracy: 0.6138, Val Loss: 1.3579, Val Accuracy: 0.5402
Epoch 2890/10000, Train Loss: 1.3225, Train Accuracy: 0.6127, Val Loss: 1.3579, Val Accuracy: 0.5402
Epoch 2891/10000, Train Loss: 1.3229, Train Accuracy: 0.6004, Val Loss: 1.3578, Val Accuracy: 0.5402
Epoch 2892/10000, Train Loss: 1.3265, Train Accuracy: 0.6027, Val Loss: 1.3578, Val Accuracy: 0.5402
Epoch 2893/10000, Train Loss: 1.3196, Train Accuracy: 0.6228, Val Loss: 1.3577, Val Accuracy: 0.5402
Epoch 2894/10000, Train Loss: 1.3332, Train Accuracy: 0.5882, Val Loss: 1.3575, Val Accuracy: 0.5402
Epoch 2895/10000, Train Loss: 1.3304, Train Accuracy: 0.6027, Val Loss: 1.3575, Val Accuracy: 0.5402
Epoch 2896/10000, Train Loss: 1.3282, Train Accuracy: 0.6138, Val Loss: 1.3574, Val Accuracy: 0.5402
Epoch 2897/10000, Train Loss: 1.3224, Train Accuracy: 0.6071, Val Loss: 1.3574, Val Accuracy: 0.5402
Epoch 2898/10000, Train Loss: 1.3222, Train Accuracy: 0.6116, Val Loss: 1.3573, Val Accuracy: 0.5402
Epoch 2899/10000, Train Loss: 1.3141, Train Accuracy: 0.6283, Val Loss: 1.3572, Val Accuracy: 0.5402
Epoch 2900/10000, Train Loss: 1.3129, Train Accuracy: 0.6295, Val Loss: 1.3571, Val Accuracy: 0.5402
Epoch 2901/10000, Train Loss: 1.3287, Train Accuracy: 0.5904, Val Loss: 1.3571, Val Accuracy: 0.5402
Epoch 2902/10000, Train Loss: 1.3215, Train Accuracy: 0.6094, Val Loss: 1.3569, Val Accuracy: 0.5402
Epoch 2903/10000, Train Loss: 1.3293, Train Accuracy: 0.6071, Val Loss: 1.3569, Val Accuracy: 0.5402
Epoch 2904/10000, Train Loss: 1.3180, Train Accuracy: 0.6172, Val Loss: 1.3568, Val Accuracy: 0.5402
Epoch 2905/10000, Train Loss: 1.3209, Train Accuracy: 0.6205, Val Loss: 1.3567, Val Accuracy: 0.5402
Epoch 2906/10000, Train Loss: 1.3167, Train Accuracy: 0.6261, Val Loss: 1.3566, Val Accuracy: 0.5402
Epoch 2907/10000, Train Loss: 1.3230, Train Accuracy: 0.6138, Val Loss: 1.3566, Val Accuracy: 0.5402
Epoch 2908/10000, Train Loss: 1.3264, Train Accuracy: 0.6127, Val Loss: 1.3566, Val Accuracy: 0.5402
Epoch 2909/10000, Train Loss: 1.3186, Train Accuracy: 0.6150, Val Loss: 1.3565, Val Accuracy: 0.5402
Epoch 2910/10000, Train Loss: 1.3293, Train Accuracy: 0.6016, Val Loss: 1.3563, Val Accuracy: 0.5402
Epoch 2911/10000, Train Loss: 1.3292, Train Accuracy: 0.6016, Val Loss: 1.3563, Val Accuracy: 0.5402
Epoch 2912/10000, Train Loss: 1.3280, Train Accuracy: 0.6071, Val Loss: 1.3561, Val Accuracy: 0.5402
Epoch 2913/10000, Train Loss: 1.3250, Train Accuracy: 0.6083, Val Loss: 1.3561, Val Accuracy: 0.5402
Epoch 2914/10000, Train Loss: 1.3183, Train Accuracy: 0.6217, Val Loss: 1.3560, Val Accuracy: 0.5402
Epoch 2915/10000, Train Loss: 1.3129, Train Accuracy: 0.6306, Val Loss: 1.3559, Val Accuracy: 0.5402
Epoch 2916/10000, Train Loss: 1.3170, Train Accuracy: 0.6272, Val Loss: 1.3559, Val Accuracy: 0.5402
Epoch 2917/10000, Train Loss: 1.3144, Train Accuracy: 0.6172, Val Loss: 1.3558, Val Accuracy: 0.5402
Epoch 2918/10000, Train Loss: 1.3191, Train Accuracy: 0.6105, Val Loss: 1.3557, Val Accuracy: 0.5402
Epoch 2919/10000, Train Loss: 1.3217, Train Accuracy: 0.6138, Val Loss: 1.3557, Val Accuracy: 0.5402
Epoch 2920/10000, Train Loss: 1.3193, Train Accuracy: 0.6161, Val Loss: 1.3555, Val Accuracy: 0.5402
Epoch 2921/10000, Train Loss: 1.3209, Train Accuracy: 0.6205, Val Loss: 1.3555, Val Accuracy: 0.5402
Epoch 2922/10000, Train Loss: 1.3079, Train Accuracy: 0.6194, Val Loss: 1.3554, Val Accuracy: 0.5402
Epoch 2923/10000, Train Loss: 1.3073, Train Accuracy: 0.6250, Val Loss: 1.3553, Val Accuracy: 0.5402
Epoch 2924/10000, Train Loss: 1.3248, Train Accuracy: 0.6071, Val Loss: 1.3552, Val Accuracy: 0.5402
Epoch 2925/10000, Train Loss: 1.3155, Train Accuracy: 0.6339, Val Loss: 1.3551, Val Accuracy: 0.5402
Epoch 2926/10000, Train Loss: 1.3126, Train Accuracy: 0.6283, Val Loss: 1.3550, Val Accuracy: 0.5402
Epoch 2927/10000, Train Loss: 1.3270, Train Accuracy: 0.6138, Val Loss: 1.3549, Val Accuracy: 0.5402
Epoch 2928/10000, Train Loss: 1.3291, Train Accuracy: 0.6004, Val Loss: 1.3548, Val Accuracy: 0.5402
Epoch 2929/10000, Train Loss: 1.3265, Train Accuracy: 0.5993, Val Loss: 1.3547, Val Accuracy: 0.5402
Epoch 2930/10000, Train Loss: 1.3264, Train Accuracy: 0.6060, Val Loss: 1.3546, Val Accuracy: 0.5402
Epoch 2931/10000, Train Loss: 1.3232, Train Accuracy: 0.6205, Val Loss: 1.3546, Val Accuracy: 0.5402
Epoch 2932/10000, Train Loss: 1.3165, Train Accuracy: 0.6150, Val Loss: 1.3545, Val Accuracy: 0.5402
Epoch 2933/10000, Train Loss: 1.3160, Train Accuracy: 0.6183, Val Loss: 1.3544, Val Accuracy: 0.5402
Epoch 2934/10000, Train Loss: 1.3177, Train Accuracy: 0.6016, Val Loss: 1.3544, Val Accuracy: 0.5402
Epoch 2935/10000, Train Loss: 1.3147, Train Accuracy: 0.6183, Val Loss: 1.3543, Val Accuracy: 0.5402
Epoch 2936/10000, Train Loss: 1.3097, Train Accuracy: 0.6217, Val Loss: 1.3542, Val Accuracy: 0.5402
Epoch 2937/10000, Train Loss: 1.3254, Train Accuracy: 0.5949, Val Loss: 1.3542, Val Accuracy: 0.5402
Epoch 2938/10000, Train Loss: 1.3163, Train Accuracy: 0.6239, Val Loss: 1.3541, Val Accuracy: 0.5402
Epoch 2939/10000, Train Loss: 1.3160, Train Accuracy: 0.6283, Val Loss: 1.3540, Val Accuracy: 0.5402
Epoch 2940/10000, Train Loss: 1.3187, Train Accuracy: 0.6239, Val Loss: 1.3539, Val Accuracy: 0.5402
Epoch 2941/10000, Train Loss: 1.3259, Train Accuracy: 0.6060, Val Loss: 1.3538, Val Accuracy: 0.5402
Epoch 2942/10000, Train Loss: 1.3143, Train Accuracy: 0.6328, Val Loss: 1.3538, Val Accuracy: 0.5402
Epoch 2943/10000, Train Loss: 1.3160, Train Accuracy: 0.6261, Val Loss: 1.3537, Val Accuracy: 0.5402
Epoch 2944/10000, Train Loss: 1.3161, Train Accuracy: 0.6083, Val Loss: 1.3536, Val Accuracy: 0.5402
Epoch 2945/10000, Train Loss: 1.3245, Train Accuracy: 0.5960, Val Loss: 1.3535, Val Accuracy: 0.5402
Epoch 2946/10000, Train Loss: 1.3192, Train Accuracy: 0.6172, Val Loss: 1.3535, Val Accuracy: 0.5402
Epoch 2947/10000, Train Loss: 1.3162, Train Accuracy: 0.6161, Val Loss: 1.3534, Val Accuracy: 0.5402
Epoch 2948/10000, Train Loss: 1.3187, Train Accuracy: 0.6116, Val Loss: 1.3534, Val Accuracy: 0.5402
Epoch 2949/10000, Train Loss: 1.3200, Train Accuracy: 0.6038, Val Loss: 1.3533, Val Accuracy: 0.5446
Epoch 2950/10000, Train Loss: 1.3248, Train Accuracy: 0.6027, Val Loss: 1.3532, Val Accuracy: 0.5446
Epoch 2951/10000, Train Loss: 1.3197, Train Accuracy: 0.6049, Val Loss: 1.3532, Val Accuracy: 0.5446
Epoch 2952/10000, Train Loss: 1.3099, Train Accuracy: 0.6406, Val Loss: 1.3531, Val Accuracy: 0.5446
Epoch 2953/10000, Train Loss: 1.3192, Train Accuracy: 0.6261, Val Loss: 1.3530, Val Accuracy: 0.5446
Epoch 2954/10000, Train Loss: 1.3151, Train Accuracy: 0.6205, Val Loss: 1.3529, Val Accuracy: 0.5446
Epoch 2955/10000, Train Loss: 1.3173, Train Accuracy: 0.6038, Val Loss: 1.3529, Val Accuracy: 0.5446
Epoch 2956/10000, Train Loss: 1.3251, Train Accuracy: 0.5960, Val Loss: 1.3528, Val Accuracy: 0.5446
Epoch 2957/10000, Train Loss: 1.3151, Train Accuracy: 0.6161, Val Loss: 1.3527, Val Accuracy: 0.5446
Epoch 2958/10000, Train Loss: 1.3071, Train Accuracy: 0.6339, Val Loss: 1.3527, Val Accuracy: 0.5446
Epoch 2959/10000, Train Loss: 1.3192, Train Accuracy: 0.6116, Val Loss: 1.3526, Val Accuracy: 0.5446
Epoch 2960/10000, Train Loss: 1.3201, Train Accuracy: 0.6138, Val Loss: 1.3525, Val Accuracy: 0.5446
Epoch 2961/10000, Train Loss: 1.3085, Train Accuracy: 0.6306, Val Loss: 1.3524, Val Accuracy: 0.5446
Epoch 2962/10000, Train Loss: 1.3138, Train Accuracy: 0.6217, Val Loss: 1.3523, Val Accuracy: 0.5446
Epoch 2963/10000, Train Loss: 1.3081, Train Accuracy: 0.6272, Val Loss: 1.3522, Val Accuracy: 0.5402
Epoch 2964/10000, Train Loss: 1.3133, Train Accuracy: 0.6250, Val Loss: 1.3522, Val Accuracy: 0.5402
Epoch 2965/10000, Train Loss: 1.3224, Train Accuracy: 0.6172, Val Loss: 1.3522, Val Accuracy: 0.5446
Epoch 2966/10000, Train Loss: 1.3126, Train Accuracy: 0.6172, Val Loss: 1.3521, Val Accuracy: 0.5402
Epoch 2967/10000, Train Loss: 1.3134, Train Accuracy: 0.6016, Val Loss: 1.3520, Val Accuracy: 0.5402
Epoch 2968/10000, Train Loss: 1.3203, Train Accuracy: 0.6049, Val Loss: 1.3519, Val Accuracy: 0.5446
Epoch 2969/10000, Train Loss: 1.3182, Train Accuracy: 0.6150, Val Loss: 1.3519, Val Accuracy: 0.5446
Epoch 2970/10000, Train Loss: 1.3140, Train Accuracy: 0.6272, Val Loss: 1.3518, Val Accuracy: 0.5446
Epoch 2971/10000, Train Loss: 1.3150, Train Accuracy: 0.6228, Val Loss: 1.3518, Val Accuracy: 0.5446
Epoch 2972/10000, Train Loss: 1.3148, Train Accuracy: 0.6161, Val Loss: 1.3518, Val Accuracy: 0.5446
Epoch 2973/10000, Train Loss: 1.3111, Train Accuracy: 0.6250, Val Loss: 1.3516, Val Accuracy: 0.5446
Epoch 2974/10000, Train Loss: 1.3195, Train Accuracy: 0.6038, Val Loss: 1.3515, Val Accuracy: 0.5446
Epoch 2975/10000, Train Loss: 1.3130, Train Accuracy: 0.6283, Val Loss: 1.3515, Val Accuracy: 0.5446
Epoch 2976/10000, Train Loss: 1.3134, Train Accuracy: 0.6138, Val Loss: 1.3514, Val Accuracy: 0.5446
Epoch 2977/10000, Train Loss: 1.3091, Train Accuracy: 0.6339, Val Loss: 1.3514, Val Accuracy: 0.5446
Epoch 2978/10000, Train Loss: 1.3229, Train Accuracy: 0.5949, Val Loss: 1.3512, Val Accuracy: 0.5446
Epoch 2979/10000, Train Loss: 1.3067, Train Accuracy: 0.6384, Val Loss: 1.3512, Val Accuracy: 0.5402
Epoch 2980/10000, Train Loss: 1.3123, Train Accuracy: 0.6317, Val Loss: 1.3511, Val Accuracy: 0.5402
Epoch 2981/10000, Train Loss: 1.3159, Train Accuracy: 0.6239, Val Loss: 1.3511, Val Accuracy: 0.5402
Epoch 2982/10000, Train Loss: 1.3042, Train Accuracy: 0.6272, Val Loss: 1.3510, Val Accuracy: 0.5446
Epoch 2983/10000, Train Loss: 1.3108, Train Accuracy: 0.6183, Val Loss: 1.3508, Val Accuracy: 0.5446
Epoch 2984/10000, Train Loss: 1.3130, Train Accuracy: 0.6172, Val Loss: 1.3508, Val Accuracy: 0.5446
Epoch 2985/10000, Train Loss: 1.3139, Train Accuracy: 0.6083, Val Loss: 1.3507, Val Accuracy: 0.5446
Epoch 2986/10000, Train Loss: 1.2997, Train Accuracy: 0.6484, Val Loss: 1.3506, Val Accuracy: 0.5446
Epoch 2987/10000, Train Loss: 1.3102, Train Accuracy: 0.6172, Val Loss: 1.3505, Val Accuracy: 0.5446
Epoch 2988/10000, Train Loss: 1.3147, Train Accuracy: 0.6060, Val Loss: 1.3505, Val Accuracy: 0.5446
Epoch 2989/10000, Train Loss: 1.3156, Train Accuracy: 0.6027, Val Loss: 1.3504, Val Accuracy: 0.5446
Epoch 2990/10000, Train Loss: 1.3141, Train Accuracy: 0.6183, Val Loss: 1.3503, Val Accuracy: 0.5446
Epoch 2991/10000, Train Loss: 1.3193, Train Accuracy: 0.6138, Val Loss: 1.3502, Val Accuracy: 0.5446
Epoch 2992/10000, Train Loss: 1.3204, Train Accuracy: 0.6049, Val Loss: 1.3501, Val Accuracy: 0.5446
Epoch 2993/10000, Train Loss: 1.3136, Train Accuracy: 0.6261, Val Loss: 1.3500, Val Accuracy: 0.5446
Epoch 2994/10000, Train Loss: 1.3068, Train Accuracy: 0.6228, Val Loss: 1.3499, Val Accuracy: 0.5446
Epoch 2995/10000, Train Loss: 1.3053, Train Accuracy: 0.6306, Val Loss: 1.3499, Val Accuracy: 0.5446
Epoch 2996/10000, Train Loss: 1.3194, Train Accuracy: 0.6172, Val Loss: 1.3497, Val Accuracy: 0.5446
Epoch 2997/10000, Train Loss: 1.3101, Train Accuracy: 0.6183, Val Loss: 1.3497, Val Accuracy: 0.5446
Epoch 2998/10000, Train Loss: 1.3201, Train Accuracy: 0.6071, Val Loss: 1.3496, Val Accuracy: 0.5446
Epoch 2999/10000, Train Loss: 1.3151, Train Accuracy: 0.6161, Val Loss: 1.3496, Val Accuracy: 0.5446
Epoch 3000/10000, Train Loss: 1.3115, Train Accuracy: 0.6250, Val Loss: 1.3496, Val Accuracy: 0.5446
Epoch 3001/10000, Train Loss: 1.3049, Train Accuracy: 0.6317, Val Loss: 1.3494, Val Accuracy: 0.5446
Epoch 3002/10000, Train Loss: 1.3084, Train Accuracy: 0.6205, Val Loss: 1.3493, Val Accuracy: 0.5446
Epoch 3003/10000, Train Loss: 1.3108, Train Accuracy: 0.6161, Val Loss: 1.3493, Val Accuracy: 0.5446
Epoch 3004/10000, Train Loss: 1.3104, Train Accuracy: 0.6272, Val Loss: 1.3493, Val Accuracy: 0.5402
Epoch 3005/10000, Train Loss: 1.3137, Train Accuracy: 0.6172, Val Loss: 1.3492, Val Accuracy: 0.5402
Epoch 3006/10000, Train Loss: 1.3120, Train Accuracy: 0.6250, Val Loss: 1.3491, Val Accuracy: 0.5402
Epoch 3007/10000, Train Loss: 1.3155, Train Accuracy: 0.6183, Val Loss: 1.3490, Val Accuracy: 0.5402
Epoch 3008/10000, Train Loss: 1.3099, Train Accuracy: 0.6194, Val Loss: 1.3490, Val Accuracy: 0.5402
Epoch 3009/10000, Train Loss: 1.3166, Train Accuracy: 0.6027, Val Loss: 1.3489, Val Accuracy: 0.5402
Epoch 3010/10000, Train Loss: 1.3086, Train Accuracy: 0.6161, Val Loss: 1.3489, Val Accuracy: 0.5402
Epoch 3011/10000, Train Loss: 1.3119, Train Accuracy: 0.6183, Val Loss: 1.3488, Val Accuracy: 0.5402
Epoch 3012/10000, Train Loss: 1.3182, Train Accuracy: 0.6094, Val Loss: 1.3488, Val Accuracy: 0.5402
Epoch 3013/10000, Train Loss: 1.3156, Train Accuracy: 0.6250, Val Loss: 1.3487, Val Accuracy: 0.5402
Epoch 3014/10000, Train Loss: 1.3136, Train Accuracy: 0.6217, Val Loss: 1.3487, Val Accuracy: 0.5446
Epoch 3015/10000, Train Loss: 1.3099, Train Accuracy: 0.6350, Val Loss: 1.3486, Val Accuracy: 0.5446
Epoch 3016/10000, Train Loss: 1.3104, Train Accuracy: 0.6228, Val Loss: 1.3485, Val Accuracy: 0.5446
Epoch 3017/10000, Train Loss: 1.3139, Train Accuracy: 0.6127, Val Loss: 1.3484, Val Accuracy: 0.5446
Epoch 3018/10000, Train Loss: 1.3180, Train Accuracy: 0.6239, Val Loss: 1.3484, Val Accuracy: 0.5491
Epoch 3019/10000, Train Loss: 1.3192, Train Accuracy: 0.6105, Val Loss: 1.3483, Val Accuracy: 0.5446
Epoch 3020/10000, Train Loss: 1.3134, Train Accuracy: 0.6172, Val Loss: 1.3482, Val Accuracy: 0.5491
Epoch 3021/10000, Train Loss: 1.3173, Train Accuracy: 0.6217, Val Loss: 1.3482, Val Accuracy: 0.5491
Epoch 3022/10000, Train Loss: 1.3114, Train Accuracy: 0.6194, Val Loss: 1.3482, Val Accuracy: 0.5491
Epoch 3023/10000, Train Loss: 1.3107, Train Accuracy: 0.6150, Val Loss: 1.3481, Val Accuracy: 0.5491
Epoch 3024/10000, Train Loss: 1.3077, Train Accuracy: 0.6306, Val Loss: 1.3481, Val Accuracy: 0.5491
Epoch 3025/10000, Train Loss: 1.3055, Train Accuracy: 0.6261, Val Loss: 1.3481, Val Accuracy: 0.5491
Epoch 3026/10000, Train Loss: 1.3062, Train Accuracy: 0.6283, Val Loss: 1.3479, Val Accuracy: 0.5491
Epoch 3027/10000, Train Loss: 1.3097, Train Accuracy: 0.6250, Val Loss: 1.3478, Val Accuracy: 0.5491
Epoch 3028/10000, Train Loss: 1.2964, Train Accuracy: 0.6473, Val Loss: 1.3478, Val Accuracy: 0.5491
Epoch 3029/10000, Train Loss: 1.3078, Train Accuracy: 0.6194, Val Loss: 1.3476, Val Accuracy: 0.5491
Epoch 3030/10000, Train Loss: 1.3164, Train Accuracy: 0.6060, Val Loss: 1.3476, Val Accuracy: 0.5491
Epoch 3031/10000, Train Loss: 1.3117, Train Accuracy: 0.6217, Val Loss: 1.3475, Val Accuracy: 0.5491
Epoch 3032/10000, Train Loss: 1.3090, Train Accuracy: 0.6194, Val Loss: 1.3475, Val Accuracy: 0.5491
Epoch 3033/10000, Train Loss: 1.2963, Train Accuracy: 0.6529, Val Loss: 1.3474, Val Accuracy: 0.5491
Epoch 3034/10000, Train Loss: 1.3074, Train Accuracy: 0.6261, Val Loss: 1.3472, Val Accuracy: 0.5491
Epoch 3035/10000, Train Loss: 1.2983, Train Accuracy: 0.6350, Val Loss: 1.3471, Val Accuracy: 0.5491
Epoch 3036/10000, Train Loss: 1.3023, Train Accuracy: 0.6283, Val Loss: 1.3471, Val Accuracy: 0.5491
Epoch 3037/10000, Train Loss: 1.3119, Train Accuracy: 0.6283, Val Loss: 1.3470, Val Accuracy: 0.5491
Epoch 3038/10000, Train Loss: 1.3094, Train Accuracy: 0.6283, Val Loss: 1.3469, Val Accuracy: 0.5491
Epoch 3039/10000, Train Loss: 1.3081, Train Accuracy: 0.6261, Val Loss: 1.3468, Val Accuracy: 0.5491
Epoch 3040/10000, Train Loss: 1.3099, Train Accuracy: 0.6272, Val Loss: 1.3468, Val Accuracy: 0.5491
Epoch 3041/10000, Train Loss: 1.3002, Train Accuracy: 0.6339, Val Loss: 1.3467, Val Accuracy: 0.5491
Epoch 3042/10000, Train Loss: 1.3124, Train Accuracy: 0.6105, Val Loss: 1.3466, Val Accuracy: 0.5491
Epoch 3043/10000, Train Loss: 1.3141, Train Accuracy: 0.6217, Val Loss: 1.3465, Val Accuracy: 0.5491
Epoch 3044/10000, Train Loss: 1.3047, Train Accuracy: 0.6406, Val Loss: 1.3464, Val Accuracy: 0.5491
Epoch 3045/10000, Train Loss: 1.3014, Train Accuracy: 0.6295, Val Loss: 1.3463, Val Accuracy: 0.5491
Epoch 3046/10000, Train Loss: 1.3058, Train Accuracy: 0.6161, Val Loss: 1.3463, Val Accuracy: 0.5491
Epoch 3047/10000, Train Loss: 1.3029, Train Accuracy: 0.6183, Val Loss: 1.3462, Val Accuracy: 0.5491
Epoch 3048/10000, Train Loss: 1.3070, Train Accuracy: 0.6373, Val Loss: 1.3462, Val Accuracy: 0.5491
Epoch 3049/10000, Train Loss: 1.3050, Train Accuracy: 0.6283, Val Loss: 1.3462, Val Accuracy: 0.5491
Epoch 3050/10000, Train Loss: 1.3067, Train Accuracy: 0.6217, Val Loss: 1.3460, Val Accuracy: 0.5491
Epoch 3051/10000, Train Loss: 1.3038, Train Accuracy: 0.6272, Val Loss: 1.3459, Val Accuracy: 0.5491
Epoch 3052/10000, Train Loss: 1.3132, Train Accuracy: 0.6172, Val Loss: 1.3459, Val Accuracy: 0.5491
Epoch 3053/10000, Train Loss: 1.3036, Train Accuracy: 0.6362, Val Loss: 1.3458, Val Accuracy: 0.5491
Epoch 3054/10000, Train Loss: 1.3048, Train Accuracy: 0.6451, Val Loss: 1.3457, Val Accuracy: 0.5491
Epoch 3055/10000, Train Loss: 1.2980, Train Accuracy: 0.6306, Val Loss: 1.3457, Val Accuracy: 0.5491
Epoch 3056/10000, Train Loss: 1.3023, Train Accuracy: 0.6272, Val Loss: 1.3457, Val Accuracy: 0.5491
Epoch 3057/10000, Train Loss: 1.3075, Train Accuracy: 0.6350, Val Loss: 1.3455, Val Accuracy: 0.5491
Epoch 3058/10000, Train Loss: 1.3004, Train Accuracy: 0.6406, Val Loss: 1.3456, Val Accuracy: 0.5491
Epoch 3059/10000, Train Loss: 1.3108, Train Accuracy: 0.6194, Val Loss: 1.3454, Val Accuracy: 0.5491
Epoch 3060/10000, Train Loss: 1.3003, Train Accuracy: 0.6295, Val Loss: 1.3453, Val Accuracy: 0.5491
Epoch 3061/10000, Train Loss: 1.2988, Train Accuracy: 0.6239, Val Loss: 1.3452, Val Accuracy: 0.5491
Epoch 3062/10000, Train Loss: 1.3039, Train Accuracy: 0.6350, Val Loss: 1.3451, Val Accuracy: 0.5491
Epoch 3063/10000, Train Loss: 1.3114, Train Accuracy: 0.6272, Val Loss: 1.3451, Val Accuracy: 0.5491
Epoch 3064/10000, Train Loss: 1.3091, Train Accuracy: 0.6183, Val Loss: 1.3449, Val Accuracy: 0.5491
Epoch 3065/10000, Train Loss: 1.3073, Train Accuracy: 0.6283, Val Loss: 1.3449, Val Accuracy: 0.5491
Epoch 3066/10000, Train Loss: 1.3040, Train Accuracy: 0.6317, Val Loss: 1.3448, Val Accuracy: 0.5491
Epoch 3067/10000, Train Loss: 1.3085, Train Accuracy: 0.6138, Val Loss: 1.3447, Val Accuracy: 0.5491
Epoch 3068/10000, Train Loss: 1.3051, Train Accuracy: 0.6250, Val Loss: 1.3446, Val Accuracy: 0.5491
Epoch 3069/10000, Train Loss: 1.3041, Train Accuracy: 0.6328, Val Loss: 1.3447, Val Accuracy: 0.5491
Epoch 3070/10000, Train Loss: 1.2906, Train Accuracy: 0.6451, Val Loss: 1.3446, Val Accuracy: 0.5491
Epoch 3071/10000, Train Loss: 1.3012, Train Accuracy: 0.6261, Val Loss: 1.3445, Val Accuracy: 0.5491
Epoch 3072/10000, Train Loss: 1.3188, Train Accuracy: 0.6038, Val Loss: 1.3444, Val Accuracy: 0.5491
Epoch 3073/10000, Train Loss: 1.3089, Train Accuracy: 0.6362, Val Loss: 1.3443, Val Accuracy: 0.5491
Epoch 3074/10000, Train Loss: 1.3086, Train Accuracy: 0.6239, Val Loss: 1.3443, Val Accuracy: 0.5491
Epoch 3075/10000, Train Loss: 1.2953, Train Accuracy: 0.6350, Val Loss: 1.3443, Val Accuracy: 0.5491
Epoch 3076/10000, Train Loss: 1.3054, Train Accuracy: 0.6261, Val Loss: 1.3442, Val Accuracy: 0.5491
Epoch 3077/10000, Train Loss: 1.3003, Train Accuracy: 0.6194, Val Loss: 1.3440, Val Accuracy: 0.5491
Epoch 3078/10000, Train Loss: 1.3134, Train Accuracy: 0.6116, Val Loss: 1.3440, Val Accuracy: 0.5491
Epoch 3079/10000, Train Loss: 1.2968, Train Accuracy: 0.6496, Val Loss: 1.3439, Val Accuracy: 0.5491
Epoch 3080/10000, Train Loss: 1.3000, Train Accuracy: 0.6384, Val Loss: 1.3438, Val Accuracy: 0.5491
Epoch 3081/10000, Train Loss: 1.3159, Train Accuracy: 0.6127, Val Loss: 1.3437, Val Accuracy: 0.5491
Epoch 3082/10000, Train Loss: 1.3044, Train Accuracy: 0.6205, Val Loss: 1.3436, Val Accuracy: 0.5491
Epoch 3083/10000, Train Loss: 1.3140, Train Accuracy: 0.6083, Val Loss: 1.3436, Val Accuracy: 0.5491
Epoch 3084/10000, Train Loss: 1.3119, Train Accuracy: 0.6217, Val Loss: 1.3435, Val Accuracy: 0.5491
Epoch 3085/10000, Train Loss: 1.3048, Train Accuracy: 0.6239, Val Loss: 1.3434, Val Accuracy: 0.5491
Epoch 3086/10000, Train Loss: 1.2996, Train Accuracy: 0.6150, Val Loss: 1.3434, Val Accuracy: 0.5491
Epoch 3087/10000, Train Loss: 1.3053, Train Accuracy: 0.6138, Val Loss: 1.3433, Val Accuracy: 0.5491
Epoch 3088/10000, Train Loss: 1.2964, Train Accuracy: 0.6295, Val Loss: 1.3433, Val Accuracy: 0.5491
Epoch 3089/10000, Train Loss: 1.2966, Train Accuracy: 0.6283, Val Loss: 1.3431, Val Accuracy: 0.5491
Epoch 3090/10000, Train Loss: 1.3076, Train Accuracy: 0.6295, Val Loss: 1.3431, Val Accuracy: 0.5491
Epoch 3091/10000, Train Loss: 1.3154, Train Accuracy: 0.6083, Val Loss: 1.3430, Val Accuracy: 0.5491
Epoch 3092/10000, Train Loss: 1.2983, Train Accuracy: 0.6317, Val Loss: 1.3429, Val Accuracy: 0.5491
Epoch 3093/10000, Train Loss: 1.3023, Train Accuracy: 0.6161, Val Loss: 1.3428, Val Accuracy: 0.5491
Epoch 3094/10000, Train Loss: 1.3031, Train Accuracy: 0.6205, Val Loss: 1.3427, Val Accuracy: 0.5491
Epoch 3095/10000, Train Loss: 1.3073, Train Accuracy: 0.6239, Val Loss: 1.3427, Val Accuracy: 0.5491
Epoch 3096/10000, Train Loss: 1.3087, Train Accuracy: 0.6250, Val Loss: 1.3426, Val Accuracy: 0.5491
Epoch 3097/10000, Train Loss: 1.3015, Train Accuracy: 0.6205, Val Loss: 1.3425, Val Accuracy: 0.5491
Epoch 3098/10000, Train Loss: 1.2991, Train Accuracy: 0.6317, Val Loss: 1.3425, Val Accuracy: 0.5536
Epoch 3099/10000, Train Loss: 1.2970, Train Accuracy: 0.6384, Val Loss: 1.3424, Val Accuracy: 0.5536
Epoch 3100/10000, Train Loss: 1.2980, Train Accuracy: 0.6317, Val Loss: 1.3424, Val Accuracy: 0.5536
Epoch 3101/10000, Train Loss: 1.3138, Train Accuracy: 0.6161, Val Loss: 1.3424, Val Accuracy: 0.5536
Epoch 3102/10000, Train Loss: 1.2980, Train Accuracy: 0.6384, Val Loss: 1.3424, Val Accuracy: 0.5536
Epoch 3103/10000, Train Loss: 1.2980, Train Accuracy: 0.6217, Val Loss: 1.3423, Val Accuracy: 0.5536
Epoch 3104/10000, Train Loss: 1.2961, Train Accuracy: 0.6451, Val Loss: 1.3422, Val Accuracy: 0.5536
Epoch 3105/10000, Train Loss: 1.3029, Train Accuracy: 0.6350, Val Loss: 1.3422, Val Accuracy: 0.5536
Epoch 3106/10000, Train Loss: 1.3058, Train Accuracy: 0.6362, Val Loss: 1.3421, Val Accuracy: 0.5536
Epoch 3107/10000, Train Loss: 1.3021, Train Accuracy: 0.6272, Val Loss: 1.3420, Val Accuracy: 0.5536
Epoch 3108/10000, Train Loss: 1.2946, Train Accuracy: 0.6261, Val Loss: 1.3420, Val Accuracy: 0.5536
Epoch 3109/10000, Train Loss: 1.2947, Train Accuracy: 0.6440, Val Loss: 1.3418, Val Accuracy: 0.5536
Epoch 3110/10000, Train Loss: 1.2978, Train Accuracy: 0.6484, Val Loss: 1.3418, Val Accuracy: 0.5536
Epoch 3111/10000, Train Loss: 1.2954, Train Accuracy: 0.6429, Val Loss: 1.3417, Val Accuracy: 0.5536
Epoch 3112/10000, Train Loss: 1.2975, Train Accuracy: 0.6362, Val Loss: 1.3417, Val Accuracy: 0.5536
Epoch 3113/10000, Train Loss: 1.3075, Train Accuracy: 0.6239, Val Loss: 1.3416, Val Accuracy: 0.5536
Epoch 3114/10000, Train Loss: 1.3017, Train Accuracy: 0.6217, Val Loss: 1.3415, Val Accuracy: 0.5536
Epoch 3115/10000, Train Loss: 1.2913, Train Accuracy: 0.6451, Val Loss: 1.3415, Val Accuracy: 0.5536
Epoch 3116/10000, Train Loss: 1.2994, Train Accuracy: 0.6350, Val Loss: 1.3415, Val Accuracy: 0.5536
Epoch 3117/10000, Train Loss: 1.2923, Train Accuracy: 0.6395, Val Loss: 1.3414, Val Accuracy: 0.5536
Epoch 3118/10000, Train Loss: 1.3095, Train Accuracy: 0.6228, Val Loss: 1.3413, Val Accuracy: 0.5536
Epoch 3119/10000, Train Loss: 1.2887, Train Accuracy: 0.6373, Val Loss: 1.3412, Val Accuracy: 0.5536
Epoch 3120/10000, Train Loss: 1.3019, Train Accuracy: 0.6317, Val Loss: 1.3411, Val Accuracy: 0.5536
Epoch 3121/10000, Train Loss: 1.3067, Train Accuracy: 0.6261, Val Loss: 1.3410, Val Accuracy: 0.5536
Epoch 3122/10000, Train Loss: 1.3000, Train Accuracy: 0.6172, Val Loss: 1.3411, Val Accuracy: 0.5536
Epoch 3123/10000, Train Loss: 1.2948, Train Accuracy: 0.6362, Val Loss: 1.3410, Val Accuracy: 0.5536
Epoch 3124/10000, Train Loss: 1.2946, Train Accuracy: 0.6417, Val Loss: 1.3409, Val Accuracy: 0.5536
Epoch 3125/10000, Train Loss: 1.2983, Train Accuracy: 0.6228, Val Loss: 1.3409, Val Accuracy: 0.5536
Epoch 3126/10000, Train Loss: 1.3021, Train Accuracy: 0.6261, Val Loss: 1.3408, Val Accuracy: 0.5536
Epoch 3127/10000, Train Loss: 1.2979, Train Accuracy: 0.6362, Val Loss: 1.3407, Val Accuracy: 0.5536
Epoch 3128/10000, Train Loss: 1.2994, Train Accuracy: 0.6306, Val Loss: 1.3407, Val Accuracy: 0.5536
Epoch 3129/10000, Train Loss: 1.2984, Train Accuracy: 0.6306, Val Loss: 1.3406, Val Accuracy: 0.5536
Epoch 3130/10000, Train Loss: 1.2972, Train Accuracy: 0.6451, Val Loss: 1.3406, Val Accuracy: 0.5536
Epoch 3131/10000, Train Loss: 1.2940, Train Accuracy: 0.6373, Val Loss: 1.3405, Val Accuracy: 0.5536
Epoch 3132/10000, Train Loss: 1.3070, Train Accuracy: 0.6228, Val Loss: 1.3404, Val Accuracy: 0.5536
Epoch 3133/10000, Train Loss: 1.2982, Train Accuracy: 0.6250, Val Loss: 1.3403, Val Accuracy: 0.5536
Epoch 3134/10000, Train Loss: 1.2924, Train Accuracy: 0.6362, Val Loss: 1.3402, Val Accuracy: 0.5536
Epoch 3135/10000, Train Loss: 1.2982, Train Accuracy: 0.6250, Val Loss: 1.3402, Val Accuracy: 0.5536
Epoch 3136/10000, Train Loss: 1.3029, Train Accuracy: 0.6239, Val Loss: 1.3401, Val Accuracy: 0.5536
Epoch 3137/10000, Train Loss: 1.2900, Train Accuracy: 0.6417, Val Loss: 1.3400, Val Accuracy: 0.5536
Epoch 3138/10000, Train Loss: 1.2998, Train Accuracy: 0.6272, Val Loss: 1.3399, Val Accuracy: 0.5536
Epoch 3139/10000, Train Loss: 1.2969, Train Accuracy: 0.6429, Val Loss: 1.3398, Val Accuracy: 0.5536
Epoch 3140/10000, Train Loss: 1.2890, Train Accuracy: 0.6462, Val Loss: 1.3398, Val Accuracy: 0.5536
Epoch 3141/10000, Train Loss: 1.2917, Train Accuracy: 0.6473, Val Loss: 1.3397, Val Accuracy: 0.5536
Epoch 3142/10000, Train Loss: 1.3024, Train Accuracy: 0.6228, Val Loss: 1.3396, Val Accuracy: 0.5536
Epoch 3143/10000, Train Loss: 1.2960, Train Accuracy: 0.6417, Val Loss: 1.3396, Val Accuracy: 0.5536
Epoch 3144/10000, Train Loss: 1.2962, Train Accuracy: 0.6395, Val Loss: 1.3395, Val Accuracy: 0.5536
Epoch 3145/10000, Train Loss: 1.2981, Train Accuracy: 0.6205, Val Loss: 1.3394, Val Accuracy: 0.5536
Epoch 3146/10000, Train Loss: 1.2970, Train Accuracy: 0.6239, Val Loss: 1.3393, Val Accuracy: 0.5536
Epoch 3147/10000, Train Loss: 1.2904, Train Accuracy: 0.6473, Val Loss: 1.3392, Val Accuracy: 0.5536
Epoch 3148/10000, Train Loss: 1.2894, Train Accuracy: 0.6484, Val Loss: 1.3391, Val Accuracy: 0.5536
Epoch 3149/10000, Train Loss: 1.2903, Train Accuracy: 0.6440, Val Loss: 1.3390, Val Accuracy: 0.5536
Epoch 3150/10000, Train Loss: 1.2910, Train Accuracy: 0.6261, Val Loss: 1.3390, Val Accuracy: 0.5580
Epoch 3151/10000, Train Loss: 1.3075, Train Accuracy: 0.6183, Val Loss: 1.3390, Val Accuracy: 0.5580
Epoch 3152/10000, Train Loss: 1.3012, Train Accuracy: 0.6328, Val Loss: 1.3389, Val Accuracy: 0.5580
Epoch 3153/10000, Train Loss: 1.3027, Train Accuracy: 0.6161, Val Loss: 1.3388, Val Accuracy: 0.5536
Epoch 3154/10000, Train Loss: 1.2957, Train Accuracy: 0.6272, Val Loss: 1.3387, Val Accuracy: 0.5580
Epoch 3155/10000, Train Loss: 1.2940, Train Accuracy: 0.6295, Val Loss: 1.3387, Val Accuracy: 0.5580
Epoch 3156/10000, Train Loss: 1.2997, Train Accuracy: 0.6194, Val Loss: 1.3386, Val Accuracy: 0.5580
Epoch 3157/10000, Train Loss: 1.2920, Train Accuracy: 0.6417, Val Loss: 1.3385, Val Accuracy: 0.5580
Epoch 3158/10000, Train Loss: 1.2911, Train Accuracy: 0.6350, Val Loss: 1.3385, Val Accuracy: 0.5580
Epoch 3159/10000, Train Loss: 1.2927, Train Accuracy: 0.6417, Val Loss: 1.3385, Val Accuracy: 0.5580
Epoch 3160/10000, Train Loss: 1.2927, Train Accuracy: 0.6417, Val Loss: 1.3384, Val Accuracy: 0.5580
Epoch 3161/10000, Train Loss: 1.2937, Train Accuracy: 0.6462, Val Loss: 1.3384, Val Accuracy: 0.5580
Epoch 3162/10000, Train Loss: 1.3043, Train Accuracy: 0.6250, Val Loss: 1.3383, Val Accuracy: 0.5580
Epoch 3163/10000, Train Loss: 1.2935, Train Accuracy: 0.6362, Val Loss: 1.3383, Val Accuracy: 0.5580
Epoch 3164/10000, Train Loss: 1.2922, Train Accuracy: 0.6451, Val Loss: 1.3382, Val Accuracy: 0.5580
Epoch 3165/10000, Train Loss: 1.2969, Train Accuracy: 0.6250, Val Loss: 1.3382, Val Accuracy: 0.5580
Epoch 3166/10000, Train Loss: 1.2908, Train Accuracy: 0.6306, Val Loss: 1.3380, Val Accuracy: 0.5580
Epoch 3167/10000, Train Loss: 1.2953, Train Accuracy: 0.6261, Val Loss: 1.3379, Val Accuracy: 0.5625
Epoch 3168/10000, Train Loss: 1.2874, Train Accuracy: 0.6496, Val Loss: 1.3378, Val Accuracy: 0.5625
Epoch 3169/10000, Train Loss: 1.3066, Train Accuracy: 0.6205, Val Loss: 1.3377, Val Accuracy: 0.5625
Epoch 3170/10000, Train Loss: 1.2894, Train Accuracy: 0.6507, Val Loss: 1.3376, Val Accuracy: 0.5625
Epoch 3171/10000, Train Loss: 1.2880, Train Accuracy: 0.6451, Val Loss: 1.3376, Val Accuracy: 0.5625
Epoch 3172/10000, Train Loss: 1.2888, Train Accuracy: 0.6417, Val Loss: 1.3375, Val Accuracy: 0.5625
Epoch 3173/10000, Train Loss: 1.2926, Train Accuracy: 0.6328, Val Loss: 1.3374, Val Accuracy: 0.5625
Epoch 3174/10000, Train Loss: 1.2907, Train Accuracy: 0.6484, Val Loss: 1.3374, Val Accuracy: 0.5625
Epoch 3175/10000, Train Loss: 1.2841, Train Accuracy: 0.6462, Val Loss: 1.3372, Val Accuracy: 0.5625
Epoch 3176/10000, Train Loss: 1.2905, Train Accuracy: 0.6306, Val Loss: 1.3372, Val Accuracy: 0.5625
Epoch 3177/10000, Train Loss: 1.2806, Train Accuracy: 0.6529, Val Loss: 1.3371, Val Accuracy: 0.5625
Epoch 3178/10000, Train Loss: 1.2942, Train Accuracy: 0.6451, Val Loss: 1.3371, Val Accuracy: 0.5625
Epoch 3179/10000, Train Loss: 1.2946, Train Accuracy: 0.6440, Val Loss: 1.3370, Val Accuracy: 0.5625
Epoch 3180/10000, Train Loss: 1.2925, Train Accuracy: 0.6384, Val Loss: 1.3369, Val Accuracy: 0.5625
Epoch 3181/10000, Train Loss: 1.3013, Train Accuracy: 0.6295, Val Loss: 1.3368, Val Accuracy: 0.5625
Epoch 3182/10000, Train Loss: 1.2909, Train Accuracy: 0.6406, Val Loss: 1.3368, Val Accuracy: 0.5625
Epoch 3183/10000, Train Loss: 1.2890, Train Accuracy: 0.6618, Val Loss: 1.3367, Val Accuracy: 0.5625
Epoch 3184/10000, Train Loss: 1.2930, Train Accuracy: 0.6295, Val Loss: 1.3367, Val Accuracy: 0.5625
Epoch 3185/10000, Train Loss: 1.2836, Train Accuracy: 0.6529, Val Loss: 1.3367, Val Accuracy: 0.5625
Epoch 3186/10000, Train Loss: 1.2906, Train Accuracy: 0.6417, Val Loss: 1.3366, Val Accuracy: 0.5670
Epoch 3187/10000, Train Loss: 1.2832, Train Accuracy: 0.6529, Val Loss: 1.3365, Val Accuracy: 0.5670
Epoch 3188/10000, Train Loss: 1.2956, Train Accuracy: 0.6272, Val Loss: 1.3364, Val Accuracy: 0.5670
Epoch 3189/10000, Train Loss: 1.2888, Train Accuracy: 0.6429, Val Loss: 1.3364, Val Accuracy: 0.5670
Epoch 3190/10000, Train Loss: 1.2940, Train Accuracy: 0.6339, Val Loss: 1.3363, Val Accuracy: 0.5670
Epoch 3191/10000, Train Loss: 1.2930, Train Accuracy: 0.6473, Val Loss: 1.3362, Val Accuracy: 0.5670
Epoch 3192/10000, Train Loss: 1.2877, Train Accuracy: 0.6429, Val Loss: 1.3362, Val Accuracy: 0.5670
Epoch 3193/10000, Train Loss: 1.2914, Train Accuracy: 0.6384, Val Loss: 1.3361, Val Accuracy: 0.5670
Epoch 3194/10000, Train Loss: 1.2872, Train Accuracy: 0.6429, Val Loss: 1.3360, Val Accuracy: 0.5670
Epoch 3195/10000, Train Loss: 1.2988, Train Accuracy: 0.6272, Val Loss: 1.3359, Val Accuracy: 0.5670
Epoch 3196/10000, Train Loss: 1.2912, Train Accuracy: 0.6440, Val Loss: 1.3358, Val Accuracy: 0.5670
Epoch 3197/10000, Train Loss: 1.2941, Train Accuracy: 0.6496, Val Loss: 1.3358, Val Accuracy: 0.5670
Epoch 3198/10000, Train Loss: 1.2841, Train Accuracy: 0.6451, Val Loss: 1.3357, Val Accuracy: 0.5670
Epoch 3199/10000, Train Loss: 1.2934, Train Accuracy: 0.6350, Val Loss: 1.3357, Val Accuracy: 0.5670
Epoch 3200/10000, Train Loss: 1.2973, Train Accuracy: 0.6239, Val Loss: 1.3357, Val Accuracy: 0.5670
Epoch 3201/10000, Train Loss: 1.2877, Train Accuracy: 0.6451, Val Loss: 1.3356, Val Accuracy: 0.5670
Epoch 3202/10000, Train Loss: 1.2848, Train Accuracy: 0.6518, Val Loss: 1.3356, Val Accuracy: 0.5670
Epoch 3203/10000, Train Loss: 1.3017, Train Accuracy: 0.6150, Val Loss: 1.3356, Val Accuracy: 0.5670
Epoch 3204/10000, Train Loss: 1.2885, Train Accuracy: 0.6261, Val Loss: 1.3355, Val Accuracy: 0.5670
Epoch 3205/10000, Train Loss: 1.2813, Train Accuracy: 0.6540, Val Loss: 1.3355, Val Accuracy: 0.5670
Epoch 3206/10000, Train Loss: 1.2918, Train Accuracy: 0.6440, Val Loss: 1.3354, Val Accuracy: 0.5670
Epoch 3207/10000, Train Loss: 1.2873, Train Accuracy: 0.6473, Val Loss: 1.3353, Val Accuracy: 0.5670
Epoch 3208/10000, Train Loss: 1.2936, Train Accuracy: 0.6328, Val Loss: 1.3353, Val Accuracy: 0.5670
Epoch 3209/10000, Train Loss: 1.3001, Train Accuracy: 0.6194, Val Loss: 1.3353, Val Accuracy: 0.5670
Epoch 3210/10000, Train Loss: 1.2931, Train Accuracy: 0.6283, Val Loss: 1.3353, Val Accuracy: 0.5670
Epoch 3211/10000, Train Loss: 1.2863, Train Accuracy: 0.6350, Val Loss: 1.3352, Val Accuracy: 0.5670
Epoch 3212/10000, Train Loss: 1.2888, Train Accuracy: 0.6384, Val Loss: 1.3352, Val Accuracy: 0.5670
Epoch 3213/10000, Train Loss: 1.2909, Train Accuracy: 0.6339, Val Loss: 1.3351, Val Accuracy: 0.5670
Epoch 3214/10000, Train Loss: 1.2781, Train Accuracy: 0.6652, Val Loss: 1.3351, Val Accuracy: 0.5670
Epoch 3215/10000, Train Loss: 1.2845, Train Accuracy: 0.6451, Val Loss: 1.3350, Val Accuracy: 0.5670
Epoch 3216/10000, Train Loss: 1.2898, Train Accuracy: 0.6362, Val Loss: 1.3349, Val Accuracy: 0.5670
Epoch 3217/10000, Train Loss: 1.2825, Train Accuracy: 0.6395, Val Loss: 1.3349, Val Accuracy: 0.5670
Epoch 3218/10000, Train Loss: 1.2958, Train Accuracy: 0.6306, Val Loss: 1.3348, Val Accuracy: 0.5670
Epoch 3219/10000, Train Loss: 1.2943, Train Accuracy: 0.6194, Val Loss: 1.3347, Val Accuracy: 0.5670
Epoch 3220/10000, Train Loss: 1.2901, Train Accuracy: 0.6529, Val Loss: 1.3346, Val Accuracy: 0.5670
Epoch 3221/10000, Train Loss: 1.2918, Train Accuracy: 0.6317, Val Loss: 1.3345, Val Accuracy: 0.5670
Epoch 3222/10000, Train Loss: 1.2788, Train Accuracy: 0.6529, Val Loss: 1.3345, Val Accuracy: 0.5670
Epoch 3223/10000, Train Loss: 1.2916, Train Accuracy: 0.6328, Val Loss: 1.3344, Val Accuracy: 0.5670
Epoch 3224/10000, Train Loss: 1.2914, Train Accuracy: 0.6395, Val Loss: 1.3343, Val Accuracy: 0.5670
Epoch 3225/10000, Train Loss: 1.2968, Train Accuracy: 0.6239, Val Loss: 1.3342, Val Accuracy: 0.5670
Epoch 3226/10000, Train Loss: 1.2849, Train Accuracy: 0.6484, Val Loss: 1.3342, Val Accuracy: 0.5670
Epoch 3227/10000, Train Loss: 1.2864, Train Accuracy: 0.6484, Val Loss: 1.3342, Val Accuracy: 0.5670
Epoch 3228/10000, Train Loss: 1.2854, Train Accuracy: 0.6429, Val Loss: 1.3341, Val Accuracy: 0.5670
Epoch 3229/10000, Train Loss: 1.2904, Train Accuracy: 0.6350, Val Loss: 1.3340, Val Accuracy: 0.5714
Epoch 3230/10000, Train Loss: 1.2950, Train Accuracy: 0.6362, Val Loss: 1.3340, Val Accuracy: 0.5714
Epoch 3231/10000, Train Loss: 1.2889, Train Accuracy: 0.6362, Val Loss: 1.3339, Val Accuracy: 0.5714
Epoch 3232/10000, Train Loss: 1.2903, Train Accuracy: 0.6362, Val Loss: 1.3339, Val Accuracy: 0.5714
Epoch 3233/10000, Train Loss: 1.2892, Train Accuracy: 0.6306, Val Loss: 1.3339, Val Accuracy: 0.5714
Epoch 3234/10000, Train Loss: 1.2846, Train Accuracy: 0.6462, Val Loss: 1.3338, Val Accuracy: 0.5714
Epoch 3235/10000, Train Loss: 1.2811, Train Accuracy: 0.6618, Val Loss: 1.3338, Val Accuracy: 0.5714
Epoch 3236/10000, Train Loss: 1.2903, Train Accuracy: 0.6440, Val Loss: 1.3336, Val Accuracy: 0.5714
Epoch 3237/10000, Train Loss: 1.2856, Train Accuracy: 0.6551, Val Loss: 1.3335, Val Accuracy: 0.5714
Epoch 3238/10000, Train Loss: 1.2907, Train Accuracy: 0.6306, Val Loss: 1.3335, Val Accuracy: 0.5714
Epoch 3239/10000, Train Loss: 1.2902, Train Accuracy: 0.6373, Val Loss: 1.3334, Val Accuracy: 0.5714
Epoch 3240/10000, Train Loss: 1.2777, Train Accuracy: 0.6607, Val Loss: 1.3334, Val Accuracy: 0.5714
Epoch 3241/10000, Train Loss: 1.2730, Train Accuracy: 0.6585, Val Loss: 1.3333, Val Accuracy: 0.5714
Epoch 3242/10000, Train Loss: 1.2911, Train Accuracy: 0.6261, Val Loss: 1.3332, Val Accuracy: 0.5714
Epoch 3243/10000, Train Loss: 1.2894, Train Accuracy: 0.6473, Val Loss: 1.3331, Val Accuracy: 0.5714
Epoch 3244/10000, Train Loss: 1.2921, Train Accuracy: 0.6194, Val Loss: 1.3331, Val Accuracy: 0.5714
Epoch 3245/10000, Train Loss: 1.2933, Train Accuracy: 0.6283, Val Loss: 1.3330, Val Accuracy: 0.5714
Epoch 3246/10000, Train Loss: 1.2907, Train Accuracy: 0.6295, Val Loss: 1.3329, Val Accuracy: 0.5714
Epoch 3247/10000, Train Loss: 1.2858, Train Accuracy: 0.6440, Val Loss: 1.3329, Val Accuracy: 0.5759
Epoch 3248/10000, Train Loss: 1.2930, Train Accuracy: 0.6362, Val Loss: 1.3329, Val Accuracy: 0.5759
Epoch 3249/10000, Train Loss: 1.2874, Train Accuracy: 0.6451, Val Loss: 1.3328, Val Accuracy: 0.5759
Epoch 3250/10000, Train Loss: 1.2846, Train Accuracy: 0.6440, Val Loss: 1.3326, Val Accuracy: 0.5759
Epoch 3251/10000, Train Loss: 1.2791, Train Accuracy: 0.6529, Val Loss: 1.3325, Val Accuracy: 0.5759
Epoch 3252/10000, Train Loss: 1.2881, Train Accuracy: 0.6451, Val Loss: 1.3324, Val Accuracy: 0.5759
Epoch 3253/10000, Train Loss: 1.2887, Train Accuracy: 0.6429, Val Loss: 1.3324, Val Accuracy: 0.5759
Epoch 3254/10000, Train Loss: 1.2857, Train Accuracy: 0.6429, Val Loss: 1.3323, Val Accuracy: 0.5759
Epoch 3255/10000, Train Loss: 1.2936, Train Accuracy: 0.6395, Val Loss: 1.3322, Val Accuracy: 0.5759
Epoch 3256/10000, Train Loss: 1.2880, Train Accuracy: 0.6272, Val Loss: 1.3321, Val Accuracy: 0.5759
Epoch 3257/10000, Train Loss: 1.2798, Train Accuracy: 0.6618, Val Loss: 1.3321, Val Accuracy: 0.5759
Epoch 3258/10000, Train Loss: 1.2740, Train Accuracy: 0.6674, Val Loss: 1.3320, Val Accuracy: 0.5759
Epoch 3259/10000, Train Loss: 1.2687, Train Accuracy: 0.6696, Val Loss: 1.3319, Val Accuracy: 0.5759
Epoch 3260/10000, Train Loss: 1.2871, Train Accuracy: 0.6484, Val Loss: 1.3318, Val Accuracy: 0.5759
Epoch 3261/10000, Train Loss: 1.2805, Train Accuracy: 0.6529, Val Loss: 1.3317, Val Accuracy: 0.5759
Epoch 3262/10000, Train Loss: 1.2799, Train Accuracy: 0.6540, Val Loss: 1.3316, Val Accuracy: 0.5804
Epoch 3263/10000, Train Loss: 1.2856, Train Accuracy: 0.6362, Val Loss: 1.3316, Val Accuracy: 0.5759
Epoch 3264/10000, Train Loss: 1.2899, Train Accuracy: 0.6295, Val Loss: 1.3316, Val Accuracy: 0.5759
Epoch 3265/10000, Train Loss: 1.2887, Train Accuracy: 0.6384, Val Loss: 1.3316, Val Accuracy: 0.5759
Epoch 3266/10000, Train Loss: 1.2900, Train Accuracy: 0.6395, Val Loss: 1.3314, Val Accuracy: 0.5848
Epoch 3267/10000, Train Loss: 1.2723, Train Accuracy: 0.6674, Val Loss: 1.3313, Val Accuracy: 0.5804
Epoch 3268/10000, Train Loss: 1.2855, Train Accuracy: 0.6451, Val Loss: 1.3313, Val Accuracy: 0.5848
Epoch 3269/10000, Train Loss: 1.2793, Train Accuracy: 0.6484, Val Loss: 1.3311, Val Accuracy: 0.5848
Epoch 3270/10000, Train Loss: 1.2846, Train Accuracy: 0.6473, Val Loss: 1.3311, Val Accuracy: 0.5804
Epoch 3271/10000, Train Loss: 1.2728, Train Accuracy: 0.6585, Val Loss: 1.3311, Val Accuracy: 0.5804
Epoch 3272/10000, Train Loss: 1.2733, Train Accuracy: 0.6641, Val Loss: 1.3311, Val Accuracy: 0.5804
Epoch 3273/10000, Train Loss: 1.2771, Train Accuracy: 0.6462, Val Loss: 1.3310, Val Accuracy: 0.5804
Epoch 3274/10000, Train Loss: 1.2922, Train Accuracy: 0.6373, Val Loss: 1.3310, Val Accuracy: 0.5804
Epoch 3275/10000, Train Loss: 1.2732, Train Accuracy: 0.6708, Val Loss: 1.3310, Val Accuracy: 0.5848
Epoch 3276/10000, Train Loss: 1.2776, Train Accuracy: 0.6540, Val Loss: 1.3309, Val Accuracy: 0.5893
Epoch 3277/10000, Train Loss: 1.2792, Train Accuracy: 0.6406, Val Loss: 1.3308, Val Accuracy: 0.5848
Epoch 3278/10000, Train Loss: 1.2791, Train Accuracy: 0.6518, Val Loss: 1.3308, Val Accuracy: 0.5848
Epoch 3279/10000, Train Loss: 1.2633, Train Accuracy: 0.6752, Val Loss: 1.3308, Val Accuracy: 0.5893
Epoch 3280/10000, Train Loss: 1.2774, Train Accuracy: 0.6518, Val Loss: 1.3307, Val Accuracy: 0.5893
Epoch 3281/10000, Train Loss: 1.2816, Train Accuracy: 0.6607, Val Loss: 1.3307, Val Accuracy: 0.5893
Epoch 3282/10000, Train Loss: 1.2793, Train Accuracy: 0.6574, Val Loss: 1.3306, Val Accuracy: 0.5848
Epoch 3283/10000, Train Loss: 1.2792, Train Accuracy: 0.6462, Val Loss: 1.3305, Val Accuracy: 0.5893
Epoch 3284/10000, Train Loss: 1.2704, Train Accuracy: 0.6529, Val Loss: 1.3305, Val Accuracy: 0.5848
Epoch 3285/10000, Train Loss: 1.2758, Train Accuracy: 0.6663, Val Loss: 1.3304, Val Accuracy: 0.5848
Epoch 3286/10000, Train Loss: 1.2770, Train Accuracy: 0.6518, Val Loss: 1.3304, Val Accuracy: 0.5848
Epoch 3287/10000, Train Loss: 1.2775, Train Accuracy: 0.6496, Val Loss: 1.3304, Val Accuracy: 0.5848
Epoch 3288/10000, Train Loss: 1.2948, Train Accuracy: 0.6350, Val Loss: 1.3303, Val Accuracy: 0.5848
Epoch 3289/10000, Train Loss: 1.2764, Train Accuracy: 0.6529, Val Loss: 1.3302, Val Accuracy: 0.5848
Epoch 3290/10000, Train Loss: 1.2704, Train Accuracy: 0.6551, Val Loss: 1.3302, Val Accuracy: 0.5848
Epoch 3291/10000, Train Loss: 1.2881, Train Accuracy: 0.6384, Val Loss: 1.3302, Val Accuracy: 0.5804
Epoch 3292/10000, Train Loss: 1.2744, Train Accuracy: 0.6708, Val Loss: 1.3301, Val Accuracy: 0.5848
Epoch 3293/10000, Train Loss: 1.2849, Train Accuracy: 0.6384, Val Loss: 1.3300, Val Accuracy: 0.5804
Epoch 3294/10000, Train Loss: 1.2768, Train Accuracy: 0.6562, Val Loss: 1.3298, Val Accuracy: 0.5848
Epoch 3295/10000, Train Loss: 1.2772, Train Accuracy: 0.6607, Val Loss: 1.3298, Val Accuracy: 0.5848
Epoch 3296/10000, Train Loss: 1.2846, Train Accuracy: 0.6518, Val Loss: 1.3298, Val Accuracy: 0.5848
Epoch 3297/10000, Train Loss: 1.2905, Train Accuracy: 0.6350, Val Loss: 1.3297, Val Accuracy: 0.5848
Epoch 3298/10000, Train Loss: 1.2704, Train Accuracy: 0.6551, Val Loss: 1.3297, Val Accuracy: 0.5848
Epoch 3299/10000, Train Loss: 1.2825, Train Accuracy: 0.6440, Val Loss: 1.3296, Val Accuracy: 0.5848
Epoch 3300/10000, Train Loss: 1.2827, Train Accuracy: 0.6373, Val Loss: 1.3295, Val Accuracy: 0.5848
Epoch 3301/10000, Train Loss: 1.2903, Train Accuracy: 0.6350, Val Loss: 1.3294, Val Accuracy: 0.5848
Epoch 3302/10000, Train Loss: 1.2662, Train Accuracy: 0.6685, Val Loss: 1.3294, Val Accuracy: 0.5893
Epoch 3303/10000, Train Loss: 1.2840, Train Accuracy: 0.6496, Val Loss: 1.3292, Val Accuracy: 0.5893
Epoch 3304/10000, Train Loss: 1.2827, Train Accuracy: 0.6451, Val Loss: 1.3292, Val Accuracy: 0.5893
Epoch 3305/10000, Train Loss: 1.2863, Train Accuracy: 0.6406, Val Loss: 1.3292, Val Accuracy: 0.5848
Epoch 3306/10000, Train Loss: 1.2693, Train Accuracy: 0.6685, Val Loss: 1.3290, Val Accuracy: 0.5848
Epoch 3307/10000, Train Loss: 1.2728, Train Accuracy: 0.6473, Val Loss: 1.3290, Val Accuracy: 0.5848
Epoch 3308/10000, Train Loss: 1.2850, Train Accuracy: 0.6395, Val Loss: 1.3289, Val Accuracy: 0.5848
Epoch 3309/10000, Train Loss: 1.2855, Train Accuracy: 0.6395, Val Loss: 1.3289, Val Accuracy: 0.5848
Epoch 3310/10000, Train Loss: 1.2785, Train Accuracy: 0.6585, Val Loss: 1.3289, Val Accuracy: 0.5848
Epoch 3311/10000, Train Loss: 1.2820, Train Accuracy: 0.6652, Val Loss: 1.3289, Val Accuracy: 0.5848
Epoch 3312/10000, Train Loss: 1.2876, Train Accuracy: 0.6295, Val Loss: 1.3288, Val Accuracy: 0.5848
Epoch 3313/10000, Train Loss: 1.2804, Train Accuracy: 0.6507, Val Loss: 1.3286, Val Accuracy: 0.5848
Epoch 3314/10000, Train Loss: 1.2762, Train Accuracy: 0.6529, Val Loss: 1.3287, Val Accuracy: 0.5848
Epoch 3315/10000, Train Loss: 1.2759, Train Accuracy: 0.6562, Val Loss: 1.3286, Val Accuracy: 0.5848
Epoch 3316/10000, Train Loss: 1.2824, Train Accuracy: 0.6417, Val Loss: 1.3286, Val Accuracy: 0.5848
Epoch 3317/10000, Train Loss: 1.2854, Train Accuracy: 0.6384, Val Loss: 1.3285, Val Accuracy: 0.5848
Epoch 3318/10000, Train Loss: 1.2807, Train Accuracy: 0.6551, Val Loss: 1.3285, Val Accuracy: 0.5848
Epoch 3319/10000, Train Loss: 1.2698, Train Accuracy: 0.6763, Val Loss: 1.3284, Val Accuracy: 0.5848
Epoch 3320/10000, Train Loss: 1.2747, Train Accuracy: 0.6618, Val Loss: 1.3284, Val Accuracy: 0.5848
Epoch 3321/10000, Train Loss: 1.2833, Train Accuracy: 0.6373, Val Loss: 1.3284, Val Accuracy: 0.5848
Epoch 3322/10000, Train Loss: 1.2783, Train Accuracy: 0.6406, Val Loss: 1.3283, Val Accuracy: 0.5848
Epoch 3323/10000, Train Loss: 1.2864, Train Accuracy: 0.6306, Val Loss: 1.3282, Val Accuracy: 0.5848
Epoch 3324/10000, Train Loss: 1.2656, Train Accuracy: 0.6730, Val Loss: 1.3282, Val Accuracy: 0.5848
Epoch 3325/10000, Train Loss: 1.2744, Train Accuracy: 0.6551, Val Loss: 1.3283, Val Accuracy: 0.5848
Epoch 3326/10000, Train Loss: 1.2852, Train Accuracy: 0.6384, Val Loss: 1.3282, Val Accuracy: 0.5893
Epoch 3327/10000, Train Loss: 1.2763, Train Accuracy: 0.6417, Val Loss: 1.3282, Val Accuracy: 0.5848
Epoch 3328/10000, Train Loss: 1.2776, Train Accuracy: 0.6507, Val Loss: 1.3282, Val Accuracy: 0.5848
Epoch 3329/10000, Train Loss: 1.2682, Train Accuracy: 0.6629, Val Loss: 1.3281, Val Accuracy: 0.5848
Epoch 3330/10000, Train Loss: 1.2720, Train Accuracy: 0.6529, Val Loss: 1.3279, Val Accuracy: 0.5848
Epoch 3331/10000, Train Loss: 1.2806, Train Accuracy: 0.6451, Val Loss: 1.3278, Val Accuracy: 0.5848
Epoch 3332/10000, Train Loss: 1.2685, Train Accuracy: 0.6674, Val Loss: 1.3277, Val Accuracy: 0.5848
Epoch 3333/10000, Train Loss: 1.2815, Train Accuracy: 0.6440, Val Loss: 1.3276, Val Accuracy: 0.5848
Epoch 3334/10000, Train Loss: 1.2722, Train Accuracy: 0.6585, Val Loss: 1.3275, Val Accuracy: 0.5848
Epoch 3335/10000, Train Loss: 1.2711, Train Accuracy: 0.6529, Val Loss: 1.3274, Val Accuracy: 0.5848
Epoch 3336/10000, Train Loss: 1.2764, Train Accuracy: 0.6607, Val Loss: 1.3274, Val Accuracy: 0.5848
Epoch 3337/10000, Train Loss: 1.2759, Train Accuracy: 0.6585, Val Loss: 1.3273, Val Accuracy: 0.5804
Epoch 3338/10000, Train Loss: 1.2656, Train Accuracy: 0.6574, Val Loss: 1.3273, Val Accuracy: 0.5848
Epoch 3339/10000, Train Loss: 1.2781, Train Accuracy: 0.6484, Val Loss: 1.3272, Val Accuracy: 0.5848
Epoch 3340/10000, Train Loss: 1.2801, Train Accuracy: 0.6373, Val Loss: 1.3272, Val Accuracy: 0.5848
Epoch 3341/10000, Train Loss: 1.2787, Train Accuracy: 0.6484, Val Loss: 1.3272, Val Accuracy: 0.5848
Epoch 3342/10000, Train Loss: 1.2737, Train Accuracy: 0.6585, Val Loss: 1.3271, Val Accuracy: 0.5848
Epoch 3343/10000, Train Loss: 1.2862, Train Accuracy: 0.6406, Val Loss: 1.3270, Val Accuracy: 0.5893
Epoch 3344/10000, Train Loss: 1.2795, Train Accuracy: 0.6585, Val Loss: 1.3270, Val Accuracy: 0.5893
Epoch 3345/10000, Train Loss: 1.2779, Train Accuracy: 0.6473, Val Loss: 1.3270, Val Accuracy: 0.5893
Epoch 3346/10000, Train Loss: 1.2734, Train Accuracy: 0.6507, Val Loss: 1.3269, Val Accuracy: 0.5848
Epoch 3347/10000, Train Loss: 1.2842, Train Accuracy: 0.6473, Val Loss: 1.3269, Val Accuracy: 0.5848
Epoch 3348/10000, Train Loss: 1.2671, Train Accuracy: 0.6674, Val Loss: 1.3269, Val Accuracy: 0.5893
Epoch 3349/10000, Train Loss: 1.2661, Train Accuracy: 0.6696, Val Loss: 1.3267, Val Accuracy: 0.5893
Epoch 3350/10000, Train Loss: 1.2771, Train Accuracy: 0.6462, Val Loss: 1.3268, Val Accuracy: 0.5893
Epoch 3351/10000, Train Loss: 1.2641, Train Accuracy: 0.6763, Val Loss: 1.3267, Val Accuracy: 0.5893
Epoch 3352/10000, Train Loss: 1.2863, Train Accuracy: 0.6429, Val Loss: 1.3267, Val Accuracy: 0.5893
Epoch 3353/10000, Train Loss: 1.2699, Train Accuracy: 0.6674, Val Loss: 1.3267, Val Accuracy: 0.5893
Epoch 3354/10000, Train Loss: 1.2811, Train Accuracy: 0.6417, Val Loss: 1.3266, Val Accuracy: 0.5938
Epoch 3355/10000, Train Loss: 1.2689, Train Accuracy: 0.6629, Val Loss: 1.3266, Val Accuracy: 0.5893
Epoch 3356/10000, Train Loss: 1.2801, Train Accuracy: 0.6507, Val Loss: 1.3265, Val Accuracy: 0.5893
Epoch 3357/10000, Train Loss: 1.2748, Train Accuracy: 0.6473, Val Loss: 1.3264, Val Accuracy: 0.5893
Epoch 3358/10000, Train Loss: 1.2716, Train Accuracy: 0.6462, Val Loss: 1.3264, Val Accuracy: 0.5893
Epoch 3359/10000, Train Loss: 1.2714, Train Accuracy: 0.6596, Val Loss: 1.3263, Val Accuracy: 0.5893
Epoch 3360/10000, Train Loss: 1.2686, Train Accuracy: 0.6741, Val Loss: 1.3262, Val Accuracy: 0.5893
Epoch 3361/10000, Train Loss: 1.2762, Train Accuracy: 0.6484, Val Loss: 1.3262, Val Accuracy: 0.5893
Epoch 3362/10000, Train Loss: 1.2577, Train Accuracy: 0.6674, Val Loss: 1.3262, Val Accuracy: 0.5893
Epoch 3363/10000, Train Loss: 1.2784, Train Accuracy: 0.6529, Val Loss: 1.3261, Val Accuracy: 0.5893
Epoch 3364/10000, Train Loss: 1.2835, Train Accuracy: 0.6451, Val Loss: 1.3260, Val Accuracy: 0.5893
Epoch 3365/10000, Train Loss: 1.2684, Train Accuracy: 0.6496, Val Loss: 1.3259, Val Accuracy: 0.5893
Epoch 3366/10000, Train Loss: 1.2714, Train Accuracy: 0.6696, Val Loss: 1.3258, Val Accuracy: 0.5893
Epoch 3367/10000, Train Loss: 1.2707, Train Accuracy: 0.6551, Val Loss: 1.3257, Val Accuracy: 0.5893
Epoch 3368/10000, Train Loss: 1.2632, Train Accuracy: 0.6629, Val Loss: 1.3257, Val Accuracy: 0.5893
Epoch 3369/10000, Train Loss: 1.2708, Train Accuracy: 0.6484, Val Loss: 1.3257, Val Accuracy: 0.5893
Epoch 3370/10000, Train Loss: 1.2729, Train Accuracy: 0.6585, Val Loss: 1.3256, Val Accuracy: 0.5893
Epoch 3371/10000, Train Loss: 1.2727, Train Accuracy: 0.6596, Val Loss: 1.3256, Val Accuracy: 0.5893
Epoch 3372/10000, Train Loss: 1.2853, Train Accuracy: 0.6362, Val Loss: 1.3255, Val Accuracy: 0.5893
Epoch 3373/10000, Train Loss: 1.2677, Train Accuracy: 0.6518, Val Loss: 1.3254, Val Accuracy: 0.5893
Epoch 3374/10000, Train Loss: 1.2787, Train Accuracy: 0.6618, Val Loss: 1.3253, Val Accuracy: 0.5893
Epoch 3375/10000, Train Loss: 1.2699, Train Accuracy: 0.6641, Val Loss: 1.3253, Val Accuracy: 0.5893
Epoch 3376/10000, Train Loss: 1.2735, Train Accuracy: 0.6518, Val Loss: 1.3252, Val Accuracy: 0.5893
Epoch 3377/10000, Train Loss: 1.2766, Train Accuracy: 0.6440, Val Loss: 1.3252, Val Accuracy: 0.5893
Epoch 3378/10000, Train Loss: 1.2871, Train Accuracy: 0.6395, Val Loss: 1.3251, Val Accuracy: 0.5893
Epoch 3379/10000, Train Loss: 1.2726, Train Accuracy: 0.6518, Val Loss: 1.3250, Val Accuracy: 0.5893
Epoch 3380/10000, Train Loss: 1.2649, Train Accuracy: 0.6629, Val Loss: 1.3250, Val Accuracy: 0.5893
Epoch 3381/10000, Train Loss: 1.2718, Train Accuracy: 0.6596, Val Loss: 1.3249, Val Accuracy: 0.5848
Epoch 3382/10000, Train Loss: 1.2674, Train Accuracy: 0.6641, Val Loss: 1.3248, Val Accuracy: 0.5893
Epoch 3383/10000, Train Loss: 1.2729, Train Accuracy: 0.6496, Val Loss: 1.3247, Val Accuracy: 0.5893
Epoch 3384/10000, Train Loss: 1.2812, Train Accuracy: 0.6373, Val Loss: 1.3247, Val Accuracy: 0.5893
Epoch 3385/10000, Train Loss: 1.2675, Train Accuracy: 0.6663, Val Loss: 1.3246, Val Accuracy: 0.5893
Epoch 3386/10000, Train Loss: 1.2710, Train Accuracy: 0.6674, Val Loss: 1.3245, Val Accuracy: 0.5848
Epoch 3387/10000, Train Loss: 1.2777, Train Accuracy: 0.6540, Val Loss: 1.3244, Val Accuracy: 0.5848
Epoch 3388/10000, Train Loss: 1.2636, Train Accuracy: 0.6618, Val Loss: 1.3245, Val Accuracy: 0.5848
Epoch 3389/10000, Train Loss: 1.2738, Train Accuracy: 0.6429, Val Loss: 1.3244, Val Accuracy: 0.5848
Epoch 3390/10000, Train Loss: 1.2713, Train Accuracy: 0.6641, Val Loss: 1.3243, Val Accuracy: 0.5848
Epoch 3391/10000, Train Loss: 1.2826, Train Accuracy: 0.6350, Val Loss: 1.3242, Val Accuracy: 0.5848
Epoch 3392/10000, Train Loss: 1.2744, Train Accuracy: 0.6395, Val Loss: 1.3242, Val Accuracy: 0.5848
Epoch 3393/10000, Train Loss: 1.2715, Train Accuracy: 0.6551, Val Loss: 1.3241, Val Accuracy: 0.5848
Epoch 3394/10000, Train Loss: 1.2637, Train Accuracy: 0.6741, Val Loss: 1.3240, Val Accuracy: 0.5848
Epoch 3395/10000, Train Loss: 1.2665, Train Accuracy: 0.6652, Val Loss: 1.3239, Val Accuracy: 0.5848
Epoch 3396/10000, Train Loss: 1.2728, Train Accuracy: 0.6417, Val Loss: 1.3239, Val Accuracy: 0.5848
Epoch 3397/10000, Train Loss: 1.2719, Train Accuracy: 0.6585, Val Loss: 1.3238, Val Accuracy: 0.5848
Epoch 3398/10000, Train Loss: 1.2718, Train Accuracy: 0.6462, Val Loss: 1.3238, Val Accuracy: 0.5848
Epoch 3399/10000, Train Loss: 1.2597, Train Accuracy: 0.6585, Val Loss: 1.3238, Val Accuracy: 0.5848
Epoch 3400/10000, Train Loss: 1.2748, Train Accuracy: 0.6629, Val Loss: 1.3238, Val Accuracy: 0.5848
Epoch 3401/10000, Train Loss: 1.2682, Train Accuracy: 0.6685, Val Loss: 1.3237, Val Accuracy: 0.5848
Epoch 3402/10000, Train Loss: 1.2666, Train Accuracy: 0.6607, Val Loss: 1.3236, Val Accuracy: 0.5848
Epoch 3403/10000, Train Loss: 1.2731, Train Accuracy: 0.6652, Val Loss: 1.3236, Val Accuracy: 0.5848
Epoch 3404/10000, Train Loss: 1.2633, Train Accuracy: 0.6763, Val Loss: 1.3236, Val Accuracy: 0.5848
Epoch 3405/10000, Train Loss: 1.2644, Train Accuracy: 0.6596, Val Loss: 1.3235, Val Accuracy: 0.5848
Epoch 3406/10000, Train Loss: 1.2686, Train Accuracy: 0.6629, Val Loss: 1.3235, Val Accuracy: 0.5848
Epoch 3407/10000, Train Loss: 1.2640, Train Accuracy: 0.6663, Val Loss: 1.3234, Val Accuracy: 0.5848
Epoch 3408/10000, Train Loss: 1.2628, Train Accuracy: 0.6708, Val Loss: 1.3235, Val Accuracy: 0.5848
Epoch 3409/10000, Train Loss: 1.2711, Train Accuracy: 0.6518, Val Loss: 1.3233, Val Accuracy: 0.5848
Epoch 3410/10000, Train Loss: 1.2719, Train Accuracy: 0.6540, Val Loss: 1.3233, Val Accuracy: 0.5848
Epoch 3411/10000, Train Loss: 1.2695, Train Accuracy: 0.6652, Val Loss: 1.3234, Val Accuracy: 0.5848
Epoch 3412/10000, Train Loss: 1.2635, Train Accuracy: 0.6641, Val Loss: 1.3233, Val Accuracy: 0.5848
Epoch 3413/10000, Train Loss: 1.2749, Train Accuracy: 0.6641, Val Loss: 1.3233, Val Accuracy: 0.5848
Epoch 3414/10000, Train Loss: 1.2703, Train Accuracy: 0.6540, Val Loss: 1.3232, Val Accuracy: 0.5848
Epoch 3415/10000, Train Loss: 1.2655, Train Accuracy: 0.6574, Val Loss: 1.3231, Val Accuracy: 0.5848
Epoch 3416/10000, Train Loss: 1.2749, Train Accuracy: 0.6507, Val Loss: 1.3230, Val Accuracy: 0.5848
Epoch 3417/10000, Train Loss: 1.2666, Train Accuracy: 0.6540, Val Loss: 1.3230, Val Accuracy: 0.5848
Epoch 3418/10000, Train Loss: 1.2656, Train Accuracy: 0.6529, Val Loss: 1.3229, Val Accuracy: 0.5848
Epoch 3419/10000, Train Loss: 1.2759, Train Accuracy: 0.6440, Val Loss: 1.3229, Val Accuracy: 0.5848
Epoch 3420/10000, Train Loss: 1.2700, Train Accuracy: 0.6585, Val Loss: 1.3228, Val Accuracy: 0.5848
Epoch 3421/10000, Train Loss: 1.2767, Train Accuracy: 0.6451, Val Loss: 1.3227, Val Accuracy: 0.5848
Epoch 3422/10000, Train Loss: 1.2806, Train Accuracy: 0.6328, Val Loss: 1.3227, Val Accuracy: 0.5848
Epoch 3423/10000, Train Loss: 1.2618, Train Accuracy: 0.6696, Val Loss: 1.3226, Val Accuracy: 0.5848
Epoch 3424/10000, Train Loss: 1.2679, Train Accuracy: 0.6674, Val Loss: 1.3226, Val Accuracy: 0.5848
Epoch 3425/10000, Train Loss: 1.2739, Train Accuracy: 0.6596, Val Loss: 1.3225, Val Accuracy: 0.5848
Epoch 3426/10000, Train Loss: 1.2717, Train Accuracy: 0.6596, Val Loss: 1.3225, Val Accuracy: 0.5848
Epoch 3427/10000, Train Loss: 1.2653, Train Accuracy: 0.6641, Val Loss: 1.3224, Val Accuracy: 0.5848
Epoch 3428/10000, Train Loss: 1.2601, Train Accuracy: 0.6652, Val Loss: 1.3223, Val Accuracy: 0.5848
Epoch 3429/10000, Train Loss: 1.2722, Train Accuracy: 0.6496, Val Loss: 1.3224, Val Accuracy: 0.5848
Epoch 3430/10000, Train Loss: 1.2698, Train Accuracy: 0.6618, Val Loss: 1.3222, Val Accuracy: 0.5848
Epoch 3431/10000, Train Loss: 1.2753, Train Accuracy: 0.6562, Val Loss: 1.3222, Val Accuracy: 0.5848
Epoch 3432/10000, Train Loss: 1.2724, Train Accuracy: 0.6484, Val Loss: 1.3221, Val Accuracy: 0.5848
Epoch 3433/10000, Train Loss: 1.2732, Train Accuracy: 0.6417, Val Loss: 1.3221, Val Accuracy: 0.5848
Epoch 3434/10000, Train Loss: 1.2728, Train Accuracy: 0.6596, Val Loss: 1.3220, Val Accuracy: 0.5848
Epoch 3435/10000, Train Loss: 1.2609, Train Accuracy: 0.6786, Val Loss: 1.3221, Val Accuracy: 0.5848
Epoch 3436/10000, Train Loss: 1.2657, Train Accuracy: 0.6685, Val Loss: 1.3220, Val Accuracy: 0.5848
Epoch 3437/10000, Train Loss: 1.2660, Train Accuracy: 0.6741, Val Loss: 1.3220, Val Accuracy: 0.5848
Epoch 3438/10000, Train Loss: 1.2760, Train Accuracy: 0.6462, Val Loss: 1.3219, Val Accuracy: 0.5848
Epoch 3439/10000, Train Loss: 1.2600, Train Accuracy: 0.6685, Val Loss: 1.3219, Val Accuracy: 0.5848
Epoch 3440/10000, Train Loss: 1.2618, Train Accuracy: 0.6663, Val Loss: 1.3218, Val Accuracy: 0.5848
Epoch 3441/10000, Train Loss: 1.2743, Train Accuracy: 0.6429, Val Loss: 1.3218, Val Accuracy: 0.5848
Epoch 3442/10000, Train Loss: 1.2669, Train Accuracy: 0.6652, Val Loss: 1.3217, Val Accuracy: 0.5848
Epoch 3443/10000, Train Loss: 1.2682, Train Accuracy: 0.6663, Val Loss: 1.3217, Val Accuracy: 0.5848
Epoch 3444/10000, Train Loss: 1.2646, Train Accuracy: 0.6641, Val Loss: 1.3216, Val Accuracy: 0.5848
Epoch 3445/10000, Train Loss: 1.2781, Train Accuracy: 0.6339, Val Loss: 1.3216, Val Accuracy: 0.5848
Epoch 3446/10000, Train Loss: 1.2659, Train Accuracy: 0.6596, Val Loss: 1.3215, Val Accuracy: 0.5848
Epoch 3447/10000, Train Loss: 1.2626, Train Accuracy: 0.6641, Val Loss: 1.3215, Val Accuracy: 0.5848
Epoch 3448/10000, Train Loss: 1.2522, Train Accuracy: 0.6708, Val Loss: 1.3214, Val Accuracy: 0.5848
Epoch 3449/10000, Train Loss: 1.2615, Train Accuracy: 0.6562, Val Loss: 1.3214, Val Accuracy: 0.5848
Epoch 3450/10000, Train Loss: 1.2708, Train Accuracy: 0.6629, Val Loss: 1.3214, Val Accuracy: 0.5848
Epoch 3451/10000, Train Loss: 1.2663, Train Accuracy: 0.6596, Val Loss: 1.3213, Val Accuracy: 0.5848
Epoch 3452/10000, Train Loss: 1.2622, Train Accuracy: 0.6663, Val Loss: 1.3212, Val Accuracy: 0.5848
Epoch 3453/10000, Train Loss: 1.2478, Train Accuracy: 0.6842, Val Loss: 1.3211, Val Accuracy: 0.5848
Epoch 3454/10000, Train Loss: 1.2605, Train Accuracy: 0.6652, Val Loss: 1.3212, Val Accuracy: 0.5848
Epoch 3455/10000, Train Loss: 1.2652, Train Accuracy: 0.6607, Val Loss: 1.3210, Val Accuracy: 0.5848
Epoch 3456/10000, Train Loss: 1.2565, Train Accuracy: 0.6819, Val Loss: 1.3211, Val Accuracy: 0.5848
Epoch 3457/10000, Train Loss: 1.2676, Train Accuracy: 0.6540, Val Loss: 1.3209, Val Accuracy: 0.5848
Epoch 3458/10000, Train Loss: 1.2615, Train Accuracy: 0.6596, Val Loss: 1.3208, Val Accuracy: 0.5848
Epoch 3459/10000, Train Loss: 1.2625, Train Accuracy: 0.6652, Val Loss: 1.3208, Val Accuracy: 0.5848
Epoch 3460/10000, Train Loss: 1.2675, Train Accuracy: 0.6451, Val Loss: 1.3206, Val Accuracy: 0.5848
Epoch 3461/10000, Train Loss: 1.2661, Train Accuracy: 0.6618, Val Loss: 1.3206, Val Accuracy: 0.5848
Epoch 3462/10000, Train Loss: 1.2590, Train Accuracy: 0.6518, Val Loss: 1.3205, Val Accuracy: 0.5848
Epoch 3463/10000, Train Loss: 1.2623, Train Accuracy: 0.6674, Val Loss: 1.3205, Val Accuracy: 0.5848
Epoch 3464/10000, Train Loss: 1.2641, Train Accuracy: 0.6730, Val Loss: 1.3204, Val Accuracy: 0.5848
Epoch 3465/10000, Train Loss: 1.2686, Train Accuracy: 0.6618, Val Loss: 1.3204, Val Accuracy: 0.5848
Epoch 3466/10000, Train Loss: 1.2671, Train Accuracy: 0.6641, Val Loss: 1.3203, Val Accuracy: 0.5848
Epoch 3467/10000, Train Loss: 1.2682, Train Accuracy: 0.6607, Val Loss: 1.3203, Val Accuracy: 0.5848
Epoch 3468/10000, Train Loss: 1.2607, Train Accuracy: 0.6629, Val Loss: 1.3202, Val Accuracy: 0.5848
Epoch 3469/10000, Train Loss: 1.2701, Train Accuracy: 0.6551, Val Loss: 1.3200, Val Accuracy: 0.5848
Epoch 3470/10000, Train Loss: 1.2581, Train Accuracy: 0.6730, Val Loss: 1.3200, Val Accuracy: 0.5848
Epoch 3471/10000, Train Loss: 1.2661, Train Accuracy: 0.6663, Val Loss: 1.3200, Val Accuracy: 0.5848
Epoch 3472/10000, Train Loss: 1.2655, Train Accuracy: 0.6763, Val Loss: 1.3200, Val Accuracy: 0.5848
Epoch 3473/10000, Train Loss: 1.2631, Train Accuracy: 0.6607, Val Loss: 1.3198, Val Accuracy: 0.5848
Epoch 3474/10000, Train Loss: 1.2684, Train Accuracy: 0.6607, Val Loss: 1.3197, Val Accuracy: 0.5848
Epoch 3475/10000, Train Loss: 1.2746, Train Accuracy: 0.6429, Val Loss: 1.3197, Val Accuracy: 0.5848
Epoch 3476/10000, Train Loss: 1.2680, Train Accuracy: 0.6529, Val Loss: 1.3196, Val Accuracy: 0.5848
Epoch 3477/10000, Train Loss: 1.2707, Train Accuracy: 0.6518, Val Loss: 1.3196, Val Accuracy: 0.5848
Epoch 3478/10000, Train Loss: 1.2743, Train Accuracy: 0.6518, Val Loss: 1.3195, Val Accuracy: 0.5848
Epoch 3479/10000, Train Loss: 1.2590, Train Accuracy: 0.6708, Val Loss: 1.3195, Val Accuracy: 0.5848
Epoch 3480/10000, Train Loss: 1.2542, Train Accuracy: 0.6808, Val Loss: 1.3194, Val Accuracy: 0.5848
Epoch 3481/10000, Train Loss: 1.2605, Train Accuracy: 0.6696, Val Loss: 1.3193, Val Accuracy: 0.5848
Epoch 3482/10000, Train Loss: 1.2560, Train Accuracy: 0.6708, Val Loss: 1.3193, Val Accuracy: 0.5848
Epoch 3483/10000, Train Loss: 1.2654, Train Accuracy: 0.6652, Val Loss: 1.3192, Val Accuracy: 0.5848
Epoch 3484/10000, Train Loss: 1.2599, Train Accuracy: 0.6685, Val Loss: 1.3191, Val Accuracy: 0.5848
Epoch 3485/10000, Train Loss: 1.2597, Train Accuracy: 0.6596, Val Loss: 1.3190, Val Accuracy: 0.5848
Epoch 3486/10000, Train Loss: 1.2698, Train Accuracy: 0.6585, Val Loss: 1.3190, Val Accuracy: 0.5848
Epoch 3487/10000, Train Loss: 1.2624, Train Accuracy: 0.6596, Val Loss: 1.3189, Val Accuracy: 0.5848
Epoch 3488/10000, Train Loss: 1.2529, Train Accuracy: 0.6797, Val Loss: 1.3189, Val Accuracy: 0.5848
Epoch 3489/10000, Train Loss: 1.2655, Train Accuracy: 0.6473, Val Loss: 1.3189, Val Accuracy: 0.5848
Epoch 3490/10000, Train Loss: 1.2608, Train Accuracy: 0.6685, Val Loss: 1.3189, Val Accuracy: 0.5848
Epoch 3491/10000, Train Loss: 1.2558, Train Accuracy: 0.6842, Val Loss: 1.3188, Val Accuracy: 0.5848
Epoch 3492/10000, Train Loss: 1.2603, Train Accuracy: 0.6674, Val Loss: 1.3188, Val Accuracy: 0.5848
Epoch 3493/10000, Train Loss: 1.2731, Train Accuracy: 0.6518, Val Loss: 1.3187, Val Accuracy: 0.5848
Epoch 3494/10000, Train Loss: 1.2698, Train Accuracy: 0.6373, Val Loss: 1.3187, Val Accuracy: 0.5848
Epoch 3495/10000, Train Loss: 1.2723, Train Accuracy: 0.6484, Val Loss: 1.3186, Val Accuracy: 0.5848
Epoch 3496/10000, Train Loss: 1.2630, Train Accuracy: 0.6708, Val Loss: 1.3185, Val Accuracy: 0.5848
Epoch 3497/10000, Train Loss: 1.2566, Train Accuracy: 0.6719, Val Loss: 1.3184, Val Accuracy: 0.5848
Epoch 3498/10000, Train Loss: 1.2541, Train Accuracy: 0.6786, Val Loss: 1.3184, Val Accuracy: 0.5848
Epoch 3499/10000, Train Loss: 1.2533, Train Accuracy: 0.6730, Val Loss: 1.3184, Val Accuracy: 0.5848
Epoch 3500/10000, Train Loss: 1.2619, Train Accuracy: 0.6685, Val Loss: 1.3183, Val Accuracy: 0.5848
Epoch 3501/10000, Train Loss: 1.2485, Train Accuracy: 0.6886, Val Loss: 1.3183, Val Accuracy: 0.5848
Epoch 3502/10000, Train Loss: 1.2580, Train Accuracy: 0.6719, Val Loss: 1.3182, Val Accuracy: 0.5848
Epoch 3503/10000, Train Loss: 1.2670, Train Accuracy: 0.6641, Val Loss: 1.3181, Val Accuracy: 0.5848
Epoch 3504/10000, Train Loss: 1.2647, Train Accuracy: 0.6585, Val Loss: 1.3181, Val Accuracy: 0.5804
Epoch 3505/10000, Train Loss: 1.2645, Train Accuracy: 0.6607, Val Loss: 1.3181, Val Accuracy: 0.5804
Epoch 3506/10000, Train Loss: 1.2612, Train Accuracy: 0.6618, Val Loss: 1.3179, Val Accuracy: 0.5848
Epoch 3507/10000, Train Loss: 1.2673, Train Accuracy: 0.6618, Val Loss: 1.3178, Val Accuracy: 0.5848
Epoch 3508/10000, Train Loss: 1.2543, Train Accuracy: 0.6819, Val Loss: 1.3177, Val Accuracy: 0.5848
Epoch 3509/10000, Train Loss: 1.2571, Train Accuracy: 0.6663, Val Loss: 1.3177, Val Accuracy: 0.5848
Epoch 3510/10000, Train Loss: 1.2629, Train Accuracy: 0.6618, Val Loss: 1.3176, Val Accuracy: 0.5848
Epoch 3511/10000, Train Loss: 1.2687, Train Accuracy: 0.6507, Val Loss: 1.3176, Val Accuracy: 0.5804
Epoch 3512/10000, Train Loss: 1.2726, Train Accuracy: 0.6496, Val Loss: 1.3176, Val Accuracy: 0.5804
Epoch 3513/10000, Train Loss: 1.2474, Train Accuracy: 0.6886, Val Loss: 1.3176, Val Accuracy: 0.5804
Epoch 3514/10000, Train Loss: 1.2568, Train Accuracy: 0.6708, Val Loss: 1.3175, Val Accuracy: 0.5804
Epoch 3515/10000, Train Loss: 1.2630, Train Accuracy: 0.6618, Val Loss: 1.3174, Val Accuracy: 0.5848
Epoch 3516/10000, Train Loss: 1.2656, Train Accuracy: 0.6529, Val Loss: 1.3173, Val Accuracy: 0.5848
Epoch 3517/10000, Train Loss: 1.2615, Train Accuracy: 0.6551, Val Loss: 1.3172, Val Accuracy: 0.5804
Epoch 3518/10000, Train Loss: 1.2616, Train Accuracy: 0.6641, Val Loss: 1.3171, Val Accuracy: 0.5848
Epoch 3519/10000, Train Loss: 1.2589, Train Accuracy: 0.6629, Val Loss: 1.3170, Val Accuracy: 0.5804
Epoch 3520/10000, Train Loss: 1.2529, Train Accuracy: 0.6819, Val Loss: 1.3170, Val Accuracy: 0.5804
Epoch 3521/10000, Train Loss: 1.2574, Train Accuracy: 0.6629, Val Loss: 1.3169, Val Accuracy: 0.5848
Epoch 3522/10000, Train Loss: 1.2509, Train Accuracy: 0.6663, Val Loss: 1.3169, Val Accuracy: 0.5848
Epoch 3523/10000, Train Loss: 1.2564, Train Accuracy: 0.6663, Val Loss: 1.3169, Val Accuracy: 0.5848
Epoch 3524/10000, Train Loss: 1.2589, Train Accuracy: 0.6641, Val Loss: 1.3169, Val Accuracy: 0.5804
Epoch 3525/10000, Train Loss: 1.2559, Train Accuracy: 0.6641, Val Loss: 1.3169, Val Accuracy: 0.5804
Epoch 3526/10000, Train Loss: 1.2648, Train Accuracy: 0.6674, Val Loss: 1.3167, Val Accuracy: 0.5848
Epoch 3527/10000, Train Loss: 1.2577, Train Accuracy: 0.6652, Val Loss: 1.3167, Val Accuracy: 0.5848
Epoch 3528/10000, Train Loss: 1.2600, Train Accuracy: 0.6618, Val Loss: 1.3167, Val Accuracy: 0.5848
Epoch 3529/10000, Train Loss: 1.2590, Train Accuracy: 0.6551, Val Loss: 1.3167, Val Accuracy: 0.5848
Epoch 3530/10000, Train Loss: 1.2646, Train Accuracy: 0.6585, Val Loss: 1.3167, Val Accuracy: 0.5848
Epoch 3531/10000, Train Loss: 1.2520, Train Accuracy: 0.6708, Val Loss: 1.3166, Val Accuracy: 0.5848
Epoch 3532/10000, Train Loss: 1.2617, Train Accuracy: 0.6719, Val Loss: 1.3166, Val Accuracy: 0.5848
Epoch 3533/10000, Train Loss: 1.2500, Train Accuracy: 0.6775, Val Loss: 1.3165, Val Accuracy: 0.5848
Epoch 3534/10000, Train Loss: 1.2594, Train Accuracy: 0.6652, Val Loss: 1.3165, Val Accuracy: 0.5848
Epoch 3535/10000, Train Loss: 1.2537, Train Accuracy: 0.6775, Val Loss: 1.3164, Val Accuracy: 0.5848
Epoch 3536/10000, Train Loss: 1.2587, Train Accuracy: 0.6708, Val Loss: 1.3164, Val Accuracy: 0.5893
Epoch 3537/10000, Train Loss: 1.2677, Train Accuracy: 0.6585, Val Loss: 1.3163, Val Accuracy: 0.5848
Epoch 3538/10000, Train Loss: 1.2565, Train Accuracy: 0.6685, Val Loss: 1.3162, Val Accuracy: 0.5848
Epoch 3539/10000, Train Loss: 1.2610, Train Accuracy: 0.6696, Val Loss: 1.3161, Val Accuracy: 0.5848
Epoch 3540/10000, Train Loss: 1.2597, Train Accuracy: 0.6685, Val Loss: 1.3160, Val Accuracy: 0.5848
Epoch 3541/10000, Train Loss: 1.2638, Train Accuracy: 0.6618, Val Loss: 1.3159, Val Accuracy: 0.5893
Epoch 3542/10000, Train Loss: 1.2616, Train Accuracy: 0.6685, Val Loss: 1.3159, Val Accuracy: 0.5893
Epoch 3543/10000, Train Loss: 1.2594, Train Accuracy: 0.6629, Val Loss: 1.3158, Val Accuracy: 0.5938
Epoch 3544/10000, Train Loss: 1.2683, Train Accuracy: 0.6685, Val Loss: 1.3158, Val Accuracy: 0.5893
Epoch 3545/10000, Train Loss: 1.2572, Train Accuracy: 0.6696, Val Loss: 1.3157, Val Accuracy: 0.5893
Epoch 3546/10000, Train Loss: 1.2643, Train Accuracy: 0.6607, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3547/10000, Train Loss: 1.2535, Train Accuracy: 0.6685, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3548/10000, Train Loss: 1.2561, Train Accuracy: 0.6763, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3549/10000, Train Loss: 1.2644, Train Accuracy: 0.6618, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3550/10000, Train Loss: 1.2587, Train Accuracy: 0.6696, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3551/10000, Train Loss: 1.2489, Train Accuracy: 0.6808, Val Loss: 1.3156, Val Accuracy: 0.5893
Epoch 3552/10000, Train Loss: 1.2535, Train Accuracy: 0.6719, Val Loss: 1.3155, Val Accuracy: 0.5893
Epoch 3553/10000, Train Loss: 1.2635, Train Accuracy: 0.6540, Val Loss: 1.3155, Val Accuracy: 0.5893
Epoch 3554/10000, Train Loss: 1.2479, Train Accuracy: 0.6842, Val Loss: 1.3155, Val Accuracy: 0.5893
Epoch 3555/10000, Train Loss: 1.2469, Train Accuracy: 0.6864, Val Loss: 1.3153, Val Accuracy: 0.5893
Epoch 3556/10000, Train Loss: 1.2578, Train Accuracy: 0.6708, Val Loss: 1.3153, Val Accuracy: 0.5893
Epoch 3557/10000, Train Loss: 1.2503, Train Accuracy: 0.6797, Val Loss: 1.3154, Val Accuracy: 0.5893
Epoch 3558/10000, Train Loss: 1.2602, Train Accuracy: 0.6585, Val Loss: 1.3153, Val Accuracy: 0.5893
Epoch 3559/10000, Train Loss: 1.2544, Train Accuracy: 0.6663, Val Loss: 1.3151, Val Accuracy: 0.5893
Epoch 3560/10000, Train Loss: 1.2550, Train Accuracy: 0.6808, Val Loss: 1.3151, Val Accuracy: 0.5893
Epoch 3561/10000, Train Loss: 1.2489, Train Accuracy: 0.6830, Val Loss: 1.3151, Val Accuracy: 0.5893
Epoch 3562/10000, Train Loss: 1.2555, Train Accuracy: 0.6797, Val Loss: 1.3151, Val Accuracy: 0.5893
Epoch 3563/10000, Train Loss: 1.2541, Train Accuracy: 0.6585, Val Loss: 1.3150, Val Accuracy: 0.5893
Epoch 3564/10000, Train Loss: 1.2550, Train Accuracy: 0.6719, Val Loss: 1.3150, Val Accuracy: 0.5893
Epoch 3565/10000, Train Loss: 1.2603, Train Accuracy: 0.6629, Val Loss: 1.3149, Val Accuracy: 0.5893
Epoch 3566/10000, Train Loss: 1.2518, Train Accuracy: 0.6752, Val Loss: 1.3149, Val Accuracy: 0.5848
Epoch 3567/10000, Train Loss: 1.2571, Train Accuracy: 0.6730, Val Loss: 1.3148, Val Accuracy: 0.5848
Epoch 3568/10000, Train Loss: 1.2654, Train Accuracy: 0.6618, Val Loss: 1.3147, Val Accuracy: 0.5848
Epoch 3569/10000, Train Loss: 1.2607, Train Accuracy: 0.6696, Val Loss: 1.3147, Val Accuracy: 0.5848
Epoch 3570/10000, Train Loss: 1.2568, Train Accuracy: 0.6708, Val Loss: 1.3146, Val Accuracy: 0.5848
Epoch 3571/10000, Train Loss: 1.2475, Train Accuracy: 0.6908, Val Loss: 1.3146, Val Accuracy: 0.5848
Epoch 3572/10000, Train Loss: 1.2563, Train Accuracy: 0.6685, Val Loss: 1.3144, Val Accuracy: 0.5848
Epoch 3573/10000, Train Loss: 1.2600, Train Accuracy: 0.6629, Val Loss: 1.3144, Val Accuracy: 0.5848
Epoch 3574/10000, Train Loss: 1.2604, Train Accuracy: 0.6663, Val Loss: 1.3143, Val Accuracy: 0.5848
Epoch 3575/10000, Train Loss: 1.2599, Train Accuracy: 0.6562, Val Loss: 1.3143, Val Accuracy: 0.5848
Epoch 3576/10000, Train Loss: 1.2551, Train Accuracy: 0.6763, Val Loss: 1.3142, Val Accuracy: 0.5804
Epoch 3577/10000, Train Loss: 1.2514, Train Accuracy: 0.6652, Val Loss: 1.3141, Val Accuracy: 0.5804
Epoch 3578/10000, Train Loss: 1.2555, Train Accuracy: 0.6663, Val Loss: 1.3141, Val Accuracy: 0.5804
Epoch 3579/10000, Train Loss: 1.2585, Train Accuracy: 0.6618, Val Loss: 1.3141, Val Accuracy: 0.5804
Epoch 3580/10000, Train Loss: 1.2568, Train Accuracy: 0.6741, Val Loss: 1.3142, Val Accuracy: 0.5848
Epoch 3581/10000, Train Loss: 1.2623, Train Accuracy: 0.6540, Val Loss: 1.3141, Val Accuracy: 0.5804
Epoch 3582/10000, Train Loss: 1.2557, Train Accuracy: 0.6674, Val Loss: 1.3140, Val Accuracy: 0.5804
Epoch 3583/10000, Train Loss: 1.2456, Train Accuracy: 0.6797, Val Loss: 1.3140, Val Accuracy: 0.5848
Epoch 3584/10000, Train Loss: 1.2563, Train Accuracy: 0.6786, Val Loss: 1.3141, Val Accuracy: 0.5848
Epoch 3585/10000, Train Loss: 1.2611, Train Accuracy: 0.6551, Val Loss: 1.3141, Val Accuracy: 0.5848
Epoch 3586/10000, Train Loss: 1.2381, Train Accuracy: 0.6920, Val Loss: 1.3140, Val Accuracy: 0.5848
Epoch 3587/10000, Train Loss: 1.2541, Train Accuracy: 0.6663, Val Loss: 1.3139, Val Accuracy: 0.5848
Epoch 3588/10000, Train Loss: 1.2536, Train Accuracy: 0.6763, Val Loss: 1.3139, Val Accuracy: 0.5804
Epoch 3589/10000, Train Loss: 1.2489, Train Accuracy: 0.6708, Val Loss: 1.3138, Val Accuracy: 0.5804
Epoch 3590/10000, Train Loss: 1.2568, Train Accuracy: 0.6719, Val Loss: 1.3138, Val Accuracy: 0.5848
Epoch 3591/10000, Train Loss: 1.2623, Train Accuracy: 0.6652, Val Loss: 1.3137, Val Accuracy: 0.5804
Epoch 3592/10000, Train Loss: 1.2553, Train Accuracy: 0.6741, Val Loss: 1.3136, Val Accuracy: 0.5804
Epoch 3593/10000, Train Loss: 1.2528, Train Accuracy: 0.6708, Val Loss: 1.3136, Val Accuracy: 0.5804
Epoch 3594/10000, Train Loss: 1.2516, Train Accuracy: 0.6730, Val Loss: 1.3135, Val Accuracy: 0.5804
Epoch 3595/10000, Train Loss: 1.2516, Train Accuracy: 0.6696, Val Loss: 1.3133, Val Accuracy: 0.5804
Epoch 3596/10000, Train Loss: 1.2597, Train Accuracy: 0.6540, Val Loss: 1.3132, Val Accuracy: 0.5804
Epoch 3597/10000, Train Loss: 1.2438, Train Accuracy: 0.6853, Val Loss: 1.3131, Val Accuracy: 0.5804
Epoch 3598/10000, Train Loss: 1.2507, Train Accuracy: 0.6652, Val Loss: 1.3131, Val Accuracy: 0.5804
Epoch 3599/10000, Train Loss: 1.2451, Train Accuracy: 0.6908, Val Loss: 1.3130, Val Accuracy: 0.5804
Epoch 3600/10000, Train Loss: 1.2619, Train Accuracy: 0.6585, Val Loss: 1.3130, Val Accuracy: 0.5804
Epoch 3601/10000, Train Loss: 1.2509, Train Accuracy: 0.6730, Val Loss: 1.3130, Val Accuracy: 0.5804
Epoch 3602/10000, Train Loss: 1.2464, Train Accuracy: 0.6708, Val Loss: 1.3129, Val Accuracy: 0.5804
Epoch 3603/10000, Train Loss: 1.2400, Train Accuracy: 0.6819, Val Loss: 1.3128, Val Accuracy: 0.5804
Epoch 3604/10000, Train Loss: 1.2473, Train Accuracy: 0.6775, Val Loss: 1.3128, Val Accuracy: 0.5804
Epoch 3605/10000, Train Loss: 1.2569, Train Accuracy: 0.6607, Val Loss: 1.3128, Val Accuracy: 0.5848
Epoch 3606/10000, Train Loss: 1.2559, Train Accuracy: 0.6741, Val Loss: 1.3128, Val Accuracy: 0.5848
Epoch 3607/10000, Train Loss: 1.2560, Train Accuracy: 0.6685, Val Loss: 1.3128, Val Accuracy: 0.5848
Epoch 3608/10000, Train Loss: 1.2476, Train Accuracy: 0.6719, Val Loss: 1.3127, Val Accuracy: 0.5848
Epoch 3609/10000, Train Loss: 1.2506, Train Accuracy: 0.6819, Val Loss: 1.3127, Val Accuracy: 0.5848
Epoch 3610/10000, Train Loss: 1.2537, Train Accuracy: 0.6808, Val Loss: 1.3127, Val Accuracy: 0.5848
Epoch 3611/10000, Train Loss: 1.2576, Train Accuracy: 0.6674, Val Loss: 1.3127, Val Accuracy: 0.5848
Epoch 3612/10000, Train Loss: 1.2555, Train Accuracy: 0.6696, Val Loss: 1.3126, Val Accuracy: 0.5848
Epoch 3613/10000, Train Loss: 1.2527, Train Accuracy: 0.6708, Val Loss: 1.3125, Val Accuracy: 0.5848
Epoch 3614/10000, Train Loss: 1.2467, Train Accuracy: 0.6797, Val Loss: 1.3124, Val Accuracy: 0.5848
Epoch 3615/10000, Train Loss: 1.2491, Train Accuracy: 0.6775, Val Loss: 1.3124, Val Accuracy: 0.5848
Epoch 3616/10000, Train Loss: 1.2647, Train Accuracy: 0.6629, Val Loss: 1.3123, Val Accuracy: 0.5848
Epoch 3617/10000, Train Loss: 1.2525, Train Accuracy: 0.6685, Val Loss: 1.3123, Val Accuracy: 0.5848
Epoch 3618/10000, Train Loss: 1.2538, Train Accuracy: 0.6741, Val Loss: 1.3122, Val Accuracy: 0.5848
Epoch 3619/10000, Train Loss: 1.2422, Train Accuracy: 0.6819, Val Loss: 1.3122, Val Accuracy: 0.5848
Epoch 3620/10000, Train Loss: 1.2594, Train Accuracy: 0.6708, Val Loss: 1.3123, Val Accuracy: 0.5848
Epoch 3621/10000, Train Loss: 1.2495, Train Accuracy: 0.6830, Val Loss: 1.3121, Val Accuracy: 0.5848
Epoch 3622/10000, Train Loss: 1.2520, Train Accuracy: 0.6719, Val Loss: 1.3120, Val Accuracy: 0.5848
Epoch 3623/10000, Train Loss: 1.2526, Train Accuracy: 0.6931, Val Loss: 1.3119, Val Accuracy: 0.5848
Epoch 3624/10000, Train Loss: 1.2551, Train Accuracy: 0.6763, Val Loss: 1.3119, Val Accuracy: 0.5848
Epoch 3625/10000, Train Loss: 1.2513, Train Accuracy: 0.6685, Val Loss: 1.3118, Val Accuracy: 0.5848
Epoch 3626/10000, Train Loss: 1.2514, Train Accuracy: 0.6719, Val Loss: 1.3117, Val Accuracy: 0.5848
Epoch 3627/10000, Train Loss: 1.2498, Train Accuracy: 0.6886, Val Loss: 1.3118, Val Accuracy: 0.5848
Epoch 3628/10000, Train Loss: 1.2526, Train Accuracy: 0.6652, Val Loss: 1.3117, Val Accuracy: 0.5848
Epoch 3629/10000, Train Loss: 1.2486, Train Accuracy: 0.6730, Val Loss: 1.3116, Val Accuracy: 0.5848
Epoch 3630/10000, Train Loss: 1.2497, Train Accuracy: 0.6808, Val Loss: 1.3115, Val Accuracy: 0.5848
Epoch 3631/10000, Train Loss: 1.2437, Train Accuracy: 0.6842, Val Loss: 1.3115, Val Accuracy: 0.5848
Epoch 3632/10000, Train Loss: 1.2383, Train Accuracy: 0.6920, Val Loss: 1.3116, Val Accuracy: 0.5848
Epoch 3633/10000, Train Loss: 1.2399, Train Accuracy: 0.6808, Val Loss: 1.3115, Val Accuracy: 0.5848
Epoch 3634/10000, Train Loss: 1.2499, Train Accuracy: 0.6864, Val Loss: 1.3114, Val Accuracy: 0.5848
Epoch 3635/10000, Train Loss: 1.2659, Train Accuracy: 0.6484, Val Loss: 1.3114, Val Accuracy: 0.5848
Epoch 3636/10000, Train Loss: 1.2449, Train Accuracy: 0.6830, Val Loss: 1.3113, Val Accuracy: 0.5848
Epoch 3637/10000, Train Loss: 1.2544, Train Accuracy: 0.6741, Val Loss: 1.3113, Val Accuracy: 0.5848
Epoch 3638/10000, Train Loss: 1.2448, Train Accuracy: 0.6853, Val Loss: 1.3113, Val Accuracy: 0.5848
Epoch 3639/10000, Train Loss: 1.2391, Train Accuracy: 0.6931, Val Loss: 1.3112, Val Accuracy: 0.5848
Epoch 3640/10000, Train Loss: 1.2501, Train Accuracy: 0.6752, Val Loss: 1.3110, Val Accuracy: 0.5848
Epoch 3641/10000, Train Loss: 1.2393, Train Accuracy: 0.6842, Val Loss: 1.3110, Val Accuracy: 0.5848
Epoch 3642/10000, Train Loss: 1.2483, Train Accuracy: 0.6730, Val Loss: 1.3108, Val Accuracy: 0.5848
Epoch 3643/10000, Train Loss: 1.2500, Train Accuracy: 0.6775, Val Loss: 1.3109, Val Accuracy: 0.5848
Epoch 3644/10000, Train Loss: 1.2497, Train Accuracy: 0.6674, Val Loss: 1.3108, Val Accuracy: 0.5848
Epoch 3645/10000, Train Loss: 1.2385, Train Accuracy: 0.7042, Val Loss: 1.3108, Val Accuracy: 0.5848
Epoch 3646/10000, Train Loss: 1.2501, Train Accuracy: 0.6719, Val Loss: 1.3107, Val Accuracy: 0.5848
Epoch 3647/10000, Train Loss: 1.2497, Train Accuracy: 0.6875, Val Loss: 1.3106, Val Accuracy: 0.5848
Epoch 3648/10000, Train Loss: 1.2599, Train Accuracy: 0.6696, Val Loss: 1.3106, Val Accuracy: 0.5848
Epoch 3649/10000, Train Loss: 1.2428, Train Accuracy: 0.6842, Val Loss: 1.3106, Val Accuracy: 0.5848
Epoch 3650/10000, Train Loss: 1.2557, Train Accuracy: 0.6674, Val Loss: 1.3106, Val Accuracy: 0.5848
Epoch 3651/10000, Train Loss: 1.2650, Train Accuracy: 0.6596, Val Loss: 1.3105, Val Accuracy: 0.5848
Epoch 3652/10000, Train Loss: 1.2539, Train Accuracy: 0.6652, Val Loss: 1.3105, Val Accuracy: 0.5848
Epoch 3653/10000, Train Loss: 1.2355, Train Accuracy: 0.6908, Val Loss: 1.3106, Val Accuracy: 0.5848
Epoch 3654/10000, Train Loss: 1.2486, Train Accuracy: 0.6897, Val Loss: 1.3104, Val Accuracy: 0.5848
Epoch 3655/10000, Train Loss: 1.2350, Train Accuracy: 0.6975, Val Loss: 1.3105, Val Accuracy: 0.5848
Epoch 3656/10000, Train Loss: 1.2531, Train Accuracy: 0.6629, Val Loss: 1.3104, Val Accuracy: 0.5848
Epoch 3657/10000, Train Loss: 1.2411, Train Accuracy: 0.6875, Val Loss: 1.3104, Val Accuracy: 0.5848
Epoch 3658/10000, Train Loss: 1.2525, Train Accuracy: 0.6696, Val Loss: 1.3103, Val Accuracy: 0.5848
Epoch 3659/10000, Train Loss: 1.2453, Train Accuracy: 0.6730, Val Loss: 1.3102, Val Accuracy: 0.5848
Epoch 3660/10000, Train Loss: 1.2464, Train Accuracy: 0.6842, Val Loss: 1.3101, Val Accuracy: 0.5848
Epoch 3661/10000, Train Loss: 1.2541, Train Accuracy: 0.6663, Val Loss: 1.3101, Val Accuracy: 0.5848
Epoch 3662/10000, Train Loss: 1.2560, Train Accuracy: 0.6629, Val Loss: 1.3100, Val Accuracy: 0.5848
Epoch 3663/10000, Train Loss: 1.2501, Train Accuracy: 0.6696, Val Loss: 1.3099, Val Accuracy: 0.5848
Epoch 3664/10000, Train Loss: 1.2406, Train Accuracy: 0.6819, Val Loss: 1.3098, Val Accuracy: 0.5848
Epoch 3665/10000, Train Loss: 1.2528, Train Accuracy: 0.6730, Val Loss: 1.3097, Val Accuracy: 0.5848
Epoch 3666/10000, Train Loss: 1.2424, Train Accuracy: 0.6987, Val Loss: 1.3096, Val Accuracy: 0.5848
Epoch 3667/10000, Train Loss: 1.2459, Train Accuracy: 0.6931, Val Loss: 1.3096, Val Accuracy: 0.5848
Epoch 3668/10000, Train Loss: 1.2393, Train Accuracy: 0.6819, Val Loss: 1.3095, Val Accuracy: 0.5848
Epoch 3669/10000, Train Loss: 1.2413, Train Accuracy: 0.6886, Val Loss: 1.3095, Val Accuracy: 0.5848
Epoch 3670/10000, Train Loss: 1.2503, Train Accuracy: 0.6763, Val Loss: 1.3094, Val Accuracy: 0.5848
Epoch 3671/10000, Train Loss: 1.2559, Train Accuracy: 0.6652, Val Loss: 1.3092, Val Accuracy: 0.5848
Epoch 3672/10000, Train Loss: 1.2548, Train Accuracy: 0.6696, Val Loss: 1.3092, Val Accuracy: 0.5848
Epoch 3673/10000, Train Loss: 1.2572, Train Accuracy: 0.6574, Val Loss: 1.3091, Val Accuracy: 0.5848
Epoch 3674/10000, Train Loss: 1.2506, Train Accuracy: 0.6641, Val Loss: 1.3091, Val Accuracy: 0.5848
Epoch 3675/10000, Train Loss: 1.2542, Train Accuracy: 0.6708, Val Loss: 1.3090, Val Accuracy: 0.5848
Epoch 3676/10000, Train Loss: 1.2475, Train Accuracy: 0.6708, Val Loss: 1.3090, Val Accuracy: 0.5848
Epoch 3677/10000, Train Loss: 1.2562, Train Accuracy: 0.6763, Val Loss: 1.3090, Val Accuracy: 0.5848
Epoch 3678/10000, Train Loss: 1.2475, Train Accuracy: 0.6652, Val Loss: 1.3089, Val Accuracy: 0.5848
Epoch 3679/10000, Train Loss: 1.2389, Train Accuracy: 0.6864, Val Loss: 1.3089, Val Accuracy: 0.5848
Epoch 3680/10000, Train Loss: 1.2409, Train Accuracy: 0.6864, Val Loss: 1.3088, Val Accuracy: 0.5848
Epoch 3681/10000, Train Loss: 1.2330, Train Accuracy: 0.6975, Val Loss: 1.3087, Val Accuracy: 0.5848
Epoch 3682/10000, Train Loss: 1.2472, Train Accuracy: 0.6775, Val Loss: 1.3087, Val Accuracy: 0.5848
Epoch 3683/10000, Train Loss: 1.2594, Train Accuracy: 0.6551, Val Loss: 1.3086, Val Accuracy: 0.5848
Epoch 3684/10000, Train Loss: 1.2426, Train Accuracy: 0.6886, Val Loss: 1.3086, Val Accuracy: 0.5848
Epoch 3685/10000, Train Loss: 1.2533, Train Accuracy: 0.6730, Val Loss: 1.3085, Val Accuracy: 0.5848
Epoch 3686/10000, Train Loss: 1.2499, Train Accuracy: 0.6786, Val Loss: 1.3084, Val Accuracy: 0.5848
Epoch 3687/10000, Train Loss: 1.2468, Train Accuracy: 0.6853, Val Loss: 1.3084, Val Accuracy: 0.5848
Epoch 3688/10000, Train Loss: 1.2428, Train Accuracy: 0.6875, Val Loss: 1.3083, Val Accuracy: 0.5893
Epoch 3689/10000, Train Loss: 1.2499, Train Accuracy: 0.6708, Val Loss: 1.3083, Val Accuracy: 0.5938
Epoch 3690/10000, Train Loss: 1.2421, Train Accuracy: 0.6987, Val Loss: 1.3083, Val Accuracy: 0.5893
Epoch 3691/10000, Train Loss: 1.2369, Train Accuracy: 0.6908, Val Loss: 1.3082, Val Accuracy: 0.5848
Epoch 3692/10000, Train Loss: 1.2412, Train Accuracy: 0.6987, Val Loss: 1.3082, Val Accuracy: 0.5848
Epoch 3693/10000, Train Loss: 1.2523, Train Accuracy: 0.6629, Val Loss: 1.3081, Val Accuracy: 0.5848
Epoch 3694/10000, Train Loss: 1.2556, Train Accuracy: 0.6618, Val Loss: 1.3080, Val Accuracy: 0.5848
Epoch 3695/10000, Train Loss: 1.2399, Train Accuracy: 0.6964, Val Loss: 1.3080, Val Accuracy: 0.5848
Epoch 3696/10000, Train Loss: 1.2513, Train Accuracy: 0.6730, Val Loss: 1.3080, Val Accuracy: 0.5848
Epoch 3697/10000, Train Loss: 1.2378, Train Accuracy: 0.6942, Val Loss: 1.3080, Val Accuracy: 0.5848
Epoch 3698/10000, Train Loss: 1.2383, Train Accuracy: 0.6931, Val Loss: 1.3080, Val Accuracy: 0.5848
Epoch 3699/10000, Train Loss: 1.2276, Train Accuracy: 0.6987, Val Loss: 1.3079, Val Accuracy: 0.5848
Epoch 3700/10000, Train Loss: 1.2450, Train Accuracy: 0.6875, Val Loss: 1.3078, Val Accuracy: 0.5848
Epoch 3701/10000, Train Loss: 1.2529, Train Accuracy: 0.6730, Val Loss: 1.3077, Val Accuracy: 0.5848
Epoch 3702/10000, Train Loss: 1.2458, Train Accuracy: 0.6730, Val Loss: 1.3076, Val Accuracy: 0.5848
Epoch 3703/10000, Train Loss: 1.2442, Train Accuracy: 0.6752, Val Loss: 1.3076, Val Accuracy: 0.5848
Epoch 3704/10000, Train Loss: 1.2497, Train Accuracy: 0.6708, Val Loss: 1.3076, Val Accuracy: 0.5848
Epoch 3705/10000, Train Loss: 1.2541, Train Accuracy: 0.6652, Val Loss: 1.3076, Val Accuracy: 0.5848
Epoch 3706/10000, Train Loss: 1.2428, Train Accuracy: 0.6842, Val Loss: 1.3076, Val Accuracy: 0.5848
Epoch 3707/10000, Train Loss: 1.2490, Train Accuracy: 0.6752, Val Loss: 1.3075, Val Accuracy: 0.5848
Epoch 3708/10000, Train Loss: 1.2458, Train Accuracy: 0.6763, Val Loss: 1.3074, Val Accuracy: 0.5848
Epoch 3709/10000, Train Loss: 1.2443, Train Accuracy: 0.6752, Val Loss: 1.3073, Val Accuracy: 0.5848
Epoch 3710/10000, Train Loss: 1.2455, Train Accuracy: 0.6708, Val Loss: 1.3074, Val Accuracy: 0.5848
Epoch 3711/10000, Train Loss: 1.2350, Train Accuracy: 0.6920, Val Loss: 1.3072, Val Accuracy: 0.5848
Epoch 3712/10000, Train Loss: 1.2531, Train Accuracy: 0.6719, Val Loss: 1.3072, Val Accuracy: 0.5848
Epoch 3713/10000, Train Loss: 1.2456, Train Accuracy: 0.6808, Val Loss: 1.3073, Val Accuracy: 0.5848
Epoch 3714/10000, Train Loss: 1.2376, Train Accuracy: 0.6864, Val Loss: 1.3073, Val Accuracy: 0.5848
Epoch 3715/10000, Train Loss: 1.2336, Train Accuracy: 0.6920, Val Loss: 1.3072, Val Accuracy: 0.5848
Epoch 3716/10000, Train Loss: 1.2339, Train Accuracy: 0.6920, Val Loss: 1.3071, Val Accuracy: 0.5848
Epoch 3717/10000, Train Loss: 1.2373, Train Accuracy: 0.6908, Val Loss: 1.3071, Val Accuracy: 0.5848
Epoch 3718/10000, Train Loss: 1.2394, Train Accuracy: 0.6853, Val Loss: 1.3071, Val Accuracy: 0.5848
Epoch 3719/10000, Train Loss: 1.2553, Train Accuracy: 0.6763, Val Loss: 1.3071, Val Accuracy: 0.5848
Epoch 3720/10000, Train Loss: 1.2392, Train Accuracy: 0.6830, Val Loss: 1.3071, Val Accuracy: 0.5848
Epoch 3721/10000, Train Loss: 1.2593, Train Accuracy: 0.6540, Val Loss: 1.3070, Val Accuracy: 0.5848
Epoch 3722/10000, Train Loss: 1.2378, Train Accuracy: 0.6875, Val Loss: 1.3069, Val Accuracy: 0.5848
Epoch 3723/10000, Train Loss: 1.2455, Train Accuracy: 0.6842, Val Loss: 1.3068, Val Accuracy: 0.5848
Epoch 3724/10000, Train Loss: 1.2473, Train Accuracy: 0.6652, Val Loss: 1.3067, Val Accuracy: 0.5848
Epoch 3725/10000, Train Loss: 1.2416, Train Accuracy: 0.6775, Val Loss: 1.3067, Val Accuracy: 0.5848
Epoch 3726/10000, Train Loss: 1.2479, Train Accuracy: 0.6775, Val Loss: 1.3067, Val Accuracy: 0.5848
Epoch 3727/10000, Train Loss: 1.2313, Train Accuracy: 0.7009, Val Loss: 1.3066, Val Accuracy: 0.5848
Epoch 3728/10000, Train Loss: 1.2466, Train Accuracy: 0.6808, Val Loss: 1.3066, Val Accuracy: 0.5848
Epoch 3729/10000, Train Loss: 1.2473, Train Accuracy: 0.6786, Val Loss: 1.3067, Val Accuracy: 0.5848
Epoch 3730/10000, Train Loss: 1.2390, Train Accuracy: 0.6775, Val Loss: 1.3065, Val Accuracy: 0.5848
Epoch 3731/10000, Train Loss: 1.2336, Train Accuracy: 0.6830, Val Loss: 1.3064, Val Accuracy: 0.5848
Epoch 3732/10000, Train Loss: 1.2499, Train Accuracy: 0.6663, Val Loss: 1.3064, Val Accuracy: 0.5848
Epoch 3733/10000, Train Loss: 1.2392, Train Accuracy: 0.6953, Val Loss: 1.3063, Val Accuracy: 0.5848
Epoch 3734/10000, Train Loss: 1.2391, Train Accuracy: 0.6853, Val Loss: 1.3063, Val Accuracy: 0.5848
Epoch 3735/10000, Train Loss: 1.2369, Train Accuracy: 0.6808, Val Loss: 1.3063, Val Accuracy: 0.5848
Epoch 3736/10000, Train Loss: 1.2416, Train Accuracy: 0.6797, Val Loss: 1.3063, Val Accuracy: 0.5848
Epoch 3737/10000, Train Loss: 1.2475, Train Accuracy: 0.6819, Val Loss: 1.3062, Val Accuracy: 0.5848
Epoch 3738/10000, Train Loss: 1.2335, Train Accuracy: 0.6931, Val Loss: 1.3061, Val Accuracy: 0.5848
Epoch 3739/10000, Train Loss: 1.2417, Train Accuracy: 0.6897, Val Loss: 1.3060, Val Accuracy: 0.5893
Epoch 3740/10000, Train Loss: 1.2360, Train Accuracy: 0.6897, Val Loss: 1.3061, Val Accuracy: 0.5848
Epoch 3741/10000, Train Loss: 1.2493, Train Accuracy: 0.6652, Val Loss: 1.3060, Val Accuracy: 0.5848
Epoch 3742/10000, Train Loss: 1.2340, Train Accuracy: 0.6786, Val Loss: 1.3060, Val Accuracy: 0.5848
Epoch 3743/10000, Train Loss: 1.2378, Train Accuracy: 0.6797, Val Loss: 1.3060, Val Accuracy: 0.5848
Epoch 3744/10000, Train Loss: 1.2428, Train Accuracy: 0.6953, Val Loss: 1.3059, Val Accuracy: 0.5848
Epoch 3745/10000, Train Loss: 1.2326, Train Accuracy: 0.6931, Val Loss: 1.3059, Val Accuracy: 0.5848
Epoch 3746/10000, Train Loss: 1.2440, Train Accuracy: 0.6775, Val Loss: 1.3058, Val Accuracy: 0.5893
Epoch 3747/10000, Train Loss: 1.2426, Train Accuracy: 0.6741, Val Loss: 1.3058, Val Accuracy: 0.5848
Epoch 3748/10000, Train Loss: 1.2411, Train Accuracy: 0.6920, Val Loss: 1.3058, Val Accuracy: 0.5848
Epoch 3749/10000, Train Loss: 1.2433, Train Accuracy: 0.6763, Val Loss: 1.3058, Val Accuracy: 0.5848
Epoch 3750/10000, Train Loss: 1.2439, Train Accuracy: 0.6864, Val Loss: 1.3058, Val Accuracy: 0.5848
Epoch 3751/10000, Train Loss: 1.2385, Train Accuracy: 0.6808, Val Loss: 1.3058, Val Accuracy: 0.5848
Epoch 3752/10000, Train Loss: 1.2436, Train Accuracy: 0.6797, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3753/10000, Train Loss: 1.2424, Train Accuracy: 0.6864, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3754/10000, Train Loss: 1.2404, Train Accuracy: 0.6875, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3755/10000, Train Loss: 1.2382, Train Accuracy: 0.6920, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3756/10000, Train Loss: 1.2332, Train Accuracy: 0.6942, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3757/10000, Train Loss: 1.2443, Train Accuracy: 0.6775, Val Loss: 1.3057, Val Accuracy: 0.5848
Epoch 3758/10000, Train Loss: 1.2359, Train Accuracy: 0.6942, Val Loss: 1.3056, Val Accuracy: 0.5848
Epoch 3759/10000, Train Loss: 1.2533, Train Accuracy: 0.6618, Val Loss: 1.3056, Val Accuracy: 0.5848
Epoch 3760/10000, Train Loss: 1.2376, Train Accuracy: 0.6897, Val Loss: 1.3055, Val Accuracy: 0.5938
Epoch 3761/10000, Train Loss: 1.2431, Train Accuracy: 0.6819, Val Loss: 1.3054, Val Accuracy: 0.5938
Epoch 3762/10000, Train Loss: 1.2474, Train Accuracy: 0.6797, Val Loss: 1.3054, Val Accuracy: 0.5893
Epoch 3763/10000, Train Loss: 1.2285, Train Accuracy: 0.6931, Val Loss: 1.3053, Val Accuracy: 0.5893
Epoch 3764/10000, Train Loss: 1.2399, Train Accuracy: 0.6842, Val Loss: 1.3052, Val Accuracy: 0.5848
Epoch 3765/10000, Train Loss: 1.2473, Train Accuracy: 0.6875, Val Loss: 1.3051, Val Accuracy: 0.5893
Epoch 3766/10000, Train Loss: 1.2303, Train Accuracy: 0.6964, Val Loss: 1.3050, Val Accuracy: 0.5893
Epoch 3767/10000, Train Loss: 1.2366, Train Accuracy: 0.6908, Val Loss: 1.3050, Val Accuracy: 0.5893
Epoch 3768/10000, Train Loss: 1.2329, Train Accuracy: 0.6853, Val Loss: 1.3049, Val Accuracy: 0.5893
Epoch 3769/10000, Train Loss: 1.2344, Train Accuracy: 0.7054, Val Loss: 1.3049, Val Accuracy: 0.5893
Epoch 3770/10000, Train Loss: 1.2431, Train Accuracy: 0.6830, Val Loss: 1.3048, Val Accuracy: 0.5893
Epoch 3771/10000, Train Loss: 1.2489, Train Accuracy: 0.6741, Val Loss: 1.3047, Val Accuracy: 0.5938
Epoch 3772/10000, Train Loss: 1.2303, Train Accuracy: 0.7009, Val Loss: 1.3047, Val Accuracy: 0.5938
Epoch 3773/10000, Train Loss: 1.2382, Train Accuracy: 0.6975, Val Loss: 1.3047, Val Accuracy: 0.5938
Epoch 3774/10000, Train Loss: 1.2362, Train Accuracy: 0.6864, Val Loss: 1.3046, Val Accuracy: 0.5938
Epoch 3775/10000, Train Loss: 1.2432, Train Accuracy: 0.6830, Val Loss: 1.3045, Val Accuracy: 0.5938
Epoch 3776/10000, Train Loss: 1.2491, Train Accuracy: 0.6752, Val Loss: 1.3045, Val Accuracy: 0.5938
Epoch 3777/10000, Train Loss: 1.2336, Train Accuracy: 0.6875, Val Loss: 1.3045, Val Accuracy: 0.5938
Epoch 3778/10000, Train Loss: 1.2356, Train Accuracy: 0.6875, Val Loss: 1.3043, Val Accuracy: 0.5982
Epoch 3779/10000, Train Loss: 1.2543, Train Accuracy: 0.6685, Val Loss: 1.3041, Val Accuracy: 0.5982
Epoch 3780/10000, Train Loss: 1.2426, Train Accuracy: 0.6741, Val Loss: 1.3040, Val Accuracy: 0.5938
Epoch 3781/10000, Train Loss: 1.2277, Train Accuracy: 0.7065, Val Loss: 1.3039, Val Accuracy: 0.5938
Epoch 3782/10000, Train Loss: 1.2444, Train Accuracy: 0.6696, Val Loss: 1.3039, Val Accuracy: 0.5938
Epoch 3783/10000, Train Loss: 1.2426, Train Accuracy: 0.6830, Val Loss: 1.3038, Val Accuracy: 0.5938
Epoch 3784/10000, Train Loss: 1.2304, Train Accuracy: 0.6920, Val Loss: 1.3037, Val Accuracy: 0.5938
Epoch 3785/10000, Train Loss: 1.2466, Train Accuracy: 0.6663, Val Loss: 1.3038, Val Accuracy: 0.5982
Epoch 3786/10000, Train Loss: 1.2416, Train Accuracy: 0.6708, Val Loss: 1.3037, Val Accuracy: 0.5938
Epoch 3787/10000, Train Loss: 1.2400, Train Accuracy: 0.6797, Val Loss: 1.3037, Val Accuracy: 0.5938
Epoch 3788/10000, Train Loss: 1.2452, Train Accuracy: 0.6674, Val Loss: 1.3036, Val Accuracy: 0.5938
Epoch 3789/10000, Train Loss: 1.2361, Train Accuracy: 0.6897, Val Loss: 1.3037, Val Accuracy: 0.5938
Epoch 3790/10000, Train Loss: 1.2302, Train Accuracy: 0.6998, Val Loss: 1.3037, Val Accuracy: 0.5938
Epoch 3791/10000, Train Loss: 1.2399, Train Accuracy: 0.6797, Val Loss: 1.3036, Val Accuracy: 0.5982
Epoch 3792/10000, Train Loss: 1.2411, Train Accuracy: 0.6864, Val Loss: 1.3035, Val Accuracy: 0.5982
Epoch 3793/10000, Train Loss: 1.2488, Train Accuracy: 0.6652, Val Loss: 1.3034, Val Accuracy: 0.5938
Epoch 3794/10000, Train Loss: 1.2410, Train Accuracy: 0.6719, Val Loss: 1.3034, Val Accuracy: 0.5938
Epoch 3795/10000, Train Loss: 1.2354, Train Accuracy: 0.6908, Val Loss: 1.3034, Val Accuracy: 0.5938
Epoch 3796/10000, Train Loss: 1.2454, Train Accuracy: 0.6663, Val Loss: 1.3034, Val Accuracy: 0.5938
Epoch 3797/10000, Train Loss: 1.2442, Train Accuracy: 0.6786, Val Loss: 1.3033, Val Accuracy: 0.5982
Epoch 3798/10000, Train Loss: 1.2433, Train Accuracy: 0.6786, Val Loss: 1.3032, Val Accuracy: 0.5938
Epoch 3799/10000, Train Loss: 1.2423, Train Accuracy: 0.6853, Val Loss: 1.3030, Val Accuracy: 0.5893
Epoch 3800/10000, Train Loss: 1.2379, Train Accuracy: 0.6819, Val Loss: 1.3030, Val Accuracy: 0.5938
Epoch 3801/10000, Train Loss: 1.2255, Train Accuracy: 0.6953, Val Loss: 1.3029, Val Accuracy: 0.5938
Epoch 3802/10000, Train Loss: 1.2255, Train Accuracy: 0.7009, Val Loss: 1.3029, Val Accuracy: 0.5893
Epoch 3803/10000, Train Loss: 1.2403, Train Accuracy: 0.6830, Val Loss: 1.3028, Val Accuracy: 0.5893
Epoch 3804/10000, Train Loss: 1.2466, Train Accuracy: 0.6752, Val Loss: 1.3027, Val Accuracy: 0.5938
Epoch 3805/10000, Train Loss: 1.2314, Train Accuracy: 0.6864, Val Loss: 1.3027, Val Accuracy: 0.5938
Epoch 3806/10000, Train Loss: 1.2292, Train Accuracy: 0.6942, Val Loss: 1.3027, Val Accuracy: 0.5938
Epoch 3807/10000, Train Loss: 1.2293, Train Accuracy: 0.7042, Val Loss: 1.3027, Val Accuracy: 0.5938
Epoch 3808/10000, Train Loss: 1.2250, Train Accuracy: 0.7020, Val Loss: 1.3026, Val Accuracy: 0.5982
Epoch 3809/10000, Train Loss: 1.2361, Train Accuracy: 0.6786, Val Loss: 1.3027, Val Accuracy: 0.5982
Epoch 3810/10000, Train Loss: 1.2316, Train Accuracy: 0.6853, Val Loss: 1.3024, Val Accuracy: 0.5938
Epoch 3811/10000, Train Loss: 1.2439, Train Accuracy: 0.6719, Val Loss: 1.3024, Val Accuracy: 0.5938
Epoch 3812/10000, Train Loss: 1.2473, Train Accuracy: 0.6730, Val Loss: 1.3024, Val Accuracy: 0.5938
Epoch 3813/10000, Train Loss: 1.2293, Train Accuracy: 0.7031, Val Loss: 1.3024, Val Accuracy: 0.5982
Epoch 3814/10000, Train Loss: 1.2421, Train Accuracy: 0.6920, Val Loss: 1.3023, Val Accuracy: 0.5982
Epoch 3815/10000, Train Loss: 1.2333, Train Accuracy: 0.6763, Val Loss: 1.3022, Val Accuracy: 0.5982
Epoch 3816/10000, Train Loss: 1.2386, Train Accuracy: 0.6864, Val Loss: 1.3022, Val Accuracy: 0.5982
Epoch 3817/10000, Train Loss: 1.2335, Train Accuracy: 0.6908, Val Loss: 1.3021, Val Accuracy: 0.5982
Epoch 3818/10000, Train Loss: 1.2244, Train Accuracy: 0.6998, Val Loss: 1.3021, Val Accuracy: 0.5982
Epoch 3819/10000, Train Loss: 1.2295, Train Accuracy: 0.6953, Val Loss: 1.3020, Val Accuracy: 0.5982
Epoch 3820/10000, Train Loss: 1.2225, Train Accuracy: 0.7109, Val Loss: 1.3021, Val Accuracy: 0.5982
Epoch 3821/10000, Train Loss: 1.2455, Train Accuracy: 0.6685, Val Loss: 1.3020, Val Accuracy: 0.5982
Epoch 3822/10000, Train Loss: 1.2258, Train Accuracy: 0.7020, Val Loss: 1.3020, Val Accuracy: 0.5982
Epoch 3823/10000, Train Loss: 1.2456, Train Accuracy: 0.6529, Val Loss: 1.3019, Val Accuracy: 0.5982
Epoch 3824/10000, Train Loss: 1.2206, Train Accuracy: 0.7042, Val Loss: 1.3019, Val Accuracy: 0.5982
Epoch 3825/10000, Train Loss: 1.2334, Train Accuracy: 0.6920, Val Loss: 1.3018, Val Accuracy: 0.5982
Epoch 3826/10000, Train Loss: 1.2348, Train Accuracy: 0.6964, Val Loss: 1.3017, Val Accuracy: 0.5982
Epoch 3827/10000, Train Loss: 1.2449, Train Accuracy: 0.6685, Val Loss: 1.3017, Val Accuracy: 0.5982
Epoch 3828/10000, Train Loss: 1.2429, Train Accuracy: 0.6775, Val Loss: 1.3017, Val Accuracy: 0.5982
Epoch 3829/10000, Train Loss: 1.2362, Train Accuracy: 0.6931, Val Loss: 1.3016, Val Accuracy: 0.5982
Epoch 3830/10000, Train Loss: 1.2264, Train Accuracy: 0.6953, Val Loss: 1.3014, Val Accuracy: 0.5982
Epoch 3831/10000, Train Loss: 1.2332, Train Accuracy: 0.6964, Val Loss: 1.3013, Val Accuracy: 0.5982
Epoch 3832/10000, Train Loss: 1.2333, Train Accuracy: 0.6864, Val Loss: 1.3012, Val Accuracy: 0.5982
Epoch 3833/10000, Train Loss: 1.2191, Train Accuracy: 0.7188, Val Loss: 1.3012, Val Accuracy: 0.5982
Epoch 3834/10000, Train Loss: 1.2323, Train Accuracy: 0.6842, Val Loss: 1.3011, Val Accuracy: 0.5982
Epoch 3835/10000, Train Loss: 1.2371, Train Accuracy: 0.6830, Val Loss: 1.3011, Val Accuracy: 0.5938
Epoch 3836/10000, Train Loss: 1.2327, Train Accuracy: 0.6897, Val Loss: 1.3011, Val Accuracy: 0.5938
Epoch 3837/10000, Train Loss: 1.2258, Train Accuracy: 0.6931, Val Loss: 1.3009, Val Accuracy: 0.5938
Epoch 3838/10000, Train Loss: 1.2385, Train Accuracy: 0.6853, Val Loss: 1.3008, Val Accuracy: 0.5982
Epoch 3839/10000, Train Loss: 1.2317, Train Accuracy: 0.6853, Val Loss: 1.3008, Val Accuracy: 0.5982
Epoch 3840/10000, Train Loss: 1.2335, Train Accuracy: 0.6975, Val Loss: 1.3007, Val Accuracy: 0.5982
Epoch 3841/10000, Train Loss: 1.2315, Train Accuracy: 0.6987, Val Loss: 1.3007, Val Accuracy: 0.5982
Epoch 3842/10000, Train Loss: 1.2356, Train Accuracy: 0.6931, Val Loss: 1.3006, Val Accuracy: 0.5938
Epoch 3843/10000, Train Loss: 1.2214, Train Accuracy: 0.7076, Val Loss: 1.3005, Val Accuracy: 0.5938
Epoch 3844/10000, Train Loss: 1.2298, Train Accuracy: 0.6942, Val Loss: 1.3005, Val Accuracy: 0.5938
Epoch 3845/10000, Train Loss: 1.2317, Train Accuracy: 0.6942, Val Loss: 1.3005, Val Accuracy: 0.5938
Epoch 3846/10000, Train Loss: 1.2467, Train Accuracy: 0.6730, Val Loss: 1.3004, Val Accuracy: 0.5982
Epoch 3847/10000, Train Loss: 1.2440, Train Accuracy: 0.6786, Val Loss: 1.3004, Val Accuracy: 0.5938
Epoch 3848/10000, Train Loss: 1.2400, Train Accuracy: 0.6842, Val Loss: 1.3004, Val Accuracy: 0.5982
Epoch 3849/10000, Train Loss: 1.2323, Train Accuracy: 0.6920, Val Loss: 1.3003, Val Accuracy: 0.6027
Epoch 3850/10000, Train Loss: 1.2222, Train Accuracy: 0.7087, Val Loss: 1.3002, Val Accuracy: 0.6027
Epoch 3851/10000, Train Loss: 1.2418, Train Accuracy: 0.6663, Val Loss: 1.3001, Val Accuracy: 0.6027
Epoch 3852/10000, Train Loss: 1.2385, Train Accuracy: 0.6819, Val Loss: 1.3002, Val Accuracy: 0.6027
Epoch 3853/10000, Train Loss: 1.2355, Train Accuracy: 0.6819, Val Loss: 1.3002, Val Accuracy: 0.6027
Epoch 3854/10000, Train Loss: 1.2251, Train Accuracy: 0.7065, Val Loss: 1.3002, Val Accuracy: 0.6027
Epoch 3855/10000, Train Loss: 1.2450, Train Accuracy: 0.6775, Val Loss: 1.3001, Val Accuracy: 0.6027
Epoch 3856/10000, Train Loss: 1.2411, Train Accuracy: 0.6842, Val Loss: 1.3000, Val Accuracy: 0.5982
Epoch 3857/10000, Train Loss: 1.2299, Train Accuracy: 0.6931, Val Loss: 1.2999, Val Accuracy: 0.6027
Epoch 3858/10000, Train Loss: 1.2155, Train Accuracy: 0.7165, Val Loss: 1.2999, Val Accuracy: 0.5982
Epoch 3859/10000, Train Loss: 1.2353, Train Accuracy: 0.6864, Val Loss: 1.2997, Val Accuracy: 0.5982
Epoch 3860/10000, Train Loss: 1.2323, Train Accuracy: 0.6875, Val Loss: 1.2997, Val Accuracy: 0.5982
Epoch 3861/10000, Train Loss: 1.2307, Train Accuracy: 0.6920, Val Loss: 1.2995, Val Accuracy: 0.6027
Epoch 3862/10000, Train Loss: 1.2285, Train Accuracy: 0.6953, Val Loss: 1.2996, Val Accuracy: 0.5982
Epoch 3863/10000, Train Loss: 1.2212, Train Accuracy: 0.7054, Val Loss: 1.2995, Val Accuracy: 0.5982
Epoch 3864/10000, Train Loss: 1.2346, Train Accuracy: 0.6964, Val Loss: 1.2995, Val Accuracy: 0.6027
Epoch 3865/10000, Train Loss: 1.2167, Train Accuracy: 0.7121, Val Loss: 1.2994, Val Accuracy: 0.6027
Epoch 3866/10000, Train Loss: 1.2344, Train Accuracy: 0.6920, Val Loss: 1.2994, Val Accuracy: 0.6027
Epoch 3867/10000, Train Loss: 1.2260, Train Accuracy: 0.6953, Val Loss: 1.2994, Val Accuracy: 0.6027
Epoch 3868/10000, Train Loss: 1.2360, Train Accuracy: 0.6830, Val Loss: 1.2993, Val Accuracy: 0.5982
Epoch 3869/10000, Train Loss: 1.2368, Train Accuracy: 0.6886, Val Loss: 1.2993, Val Accuracy: 0.5982
Epoch 3870/10000, Train Loss: 1.2288, Train Accuracy: 0.6931, Val Loss: 1.2993, Val Accuracy: 0.5982
Epoch 3871/10000, Train Loss: 1.2354, Train Accuracy: 0.6964, Val Loss: 1.2991, Val Accuracy: 0.6027
Epoch 3872/10000, Train Loss: 1.2396, Train Accuracy: 0.6842, Val Loss: 1.2991, Val Accuracy: 0.6027
Epoch 3873/10000, Train Loss: 1.2288, Train Accuracy: 0.7054, Val Loss: 1.2992, Val Accuracy: 0.6027
Epoch 3874/10000, Train Loss: 1.2291, Train Accuracy: 0.6886, Val Loss: 1.2991, Val Accuracy: 0.6027
Epoch 3875/10000, Train Loss: 1.2378, Train Accuracy: 0.6975, Val Loss: 1.2991, Val Accuracy: 0.6027
Epoch 3876/10000, Train Loss: 1.2274, Train Accuracy: 0.6897, Val Loss: 1.2990, Val Accuracy: 0.6027
Epoch 3877/10000, Train Loss: 1.2352, Train Accuracy: 0.6908, Val Loss: 1.2989, Val Accuracy: 0.6027
Epoch 3878/10000, Train Loss: 1.2309, Train Accuracy: 0.6864, Val Loss: 1.2988, Val Accuracy: 0.6027
Epoch 3879/10000, Train Loss: 1.2380, Train Accuracy: 0.6864, Val Loss: 1.2989, Val Accuracy: 0.6027
Epoch 3880/10000, Train Loss: 1.2242, Train Accuracy: 0.6920, Val Loss: 1.2988, Val Accuracy: 0.6027
Epoch 3881/10000, Train Loss: 1.2241, Train Accuracy: 0.6975, Val Loss: 1.2988, Val Accuracy: 0.6027
Epoch 3882/10000, Train Loss: 1.2313, Train Accuracy: 0.6908, Val Loss: 1.2987, Val Accuracy: 0.6027
Epoch 3883/10000, Train Loss: 1.2234, Train Accuracy: 0.7042, Val Loss: 1.2986, Val Accuracy: 0.6027
Epoch 3884/10000, Train Loss: 1.2309, Train Accuracy: 0.6908, Val Loss: 1.2986, Val Accuracy: 0.6027
Epoch 3885/10000, Train Loss: 1.2337, Train Accuracy: 0.6797, Val Loss: 1.2985, Val Accuracy: 0.6027
Epoch 3886/10000, Train Loss: 1.2342, Train Accuracy: 0.6886, Val Loss: 1.2984, Val Accuracy: 0.6027
Epoch 3887/10000, Train Loss: 1.2309, Train Accuracy: 0.6875, Val Loss: 1.2983, Val Accuracy: 0.6027
Epoch 3888/10000, Train Loss: 1.2271, Train Accuracy: 0.6886, Val Loss: 1.2983, Val Accuracy: 0.6027
Epoch 3889/10000, Train Loss: 1.2312, Train Accuracy: 0.6908, Val Loss: 1.2982, Val Accuracy: 0.6027
Epoch 3890/10000, Train Loss: 1.2183, Train Accuracy: 0.7154, Val Loss: 1.2982, Val Accuracy: 0.6027
Epoch 3891/10000, Train Loss: 1.2247, Train Accuracy: 0.7098, Val Loss: 1.2981, Val Accuracy: 0.6027
Epoch 3892/10000, Train Loss: 1.2220, Train Accuracy: 0.7098, Val Loss: 1.2981, Val Accuracy: 0.6027
Epoch 3893/10000, Train Loss: 1.2312, Train Accuracy: 0.6853, Val Loss: 1.2979, Val Accuracy: 0.6027
Epoch 3894/10000, Train Loss: 1.2245, Train Accuracy: 0.6931, Val Loss: 1.2978, Val Accuracy: 0.6027
Epoch 3895/10000, Train Loss: 1.2152, Train Accuracy: 0.7132, Val Loss: 1.2978, Val Accuracy: 0.6027
Epoch 3896/10000, Train Loss: 1.2335, Train Accuracy: 0.6908, Val Loss: 1.2978, Val Accuracy: 0.6027
Epoch 3897/10000, Train Loss: 1.2365, Train Accuracy: 0.6897, Val Loss: 1.2977, Val Accuracy: 0.6027
Epoch 3898/10000, Train Loss: 1.2344, Train Accuracy: 0.6775, Val Loss: 1.2977, Val Accuracy: 0.6027
Epoch 3899/10000, Train Loss: 1.2253, Train Accuracy: 0.7009, Val Loss: 1.2976, Val Accuracy: 0.6027
Epoch 3900/10000, Train Loss: 1.2356, Train Accuracy: 0.6875, Val Loss: 1.2976, Val Accuracy: 0.6027
Epoch 3901/10000, Train Loss: 1.2385, Train Accuracy: 0.6685, Val Loss: 1.2975, Val Accuracy: 0.6027
Epoch 3902/10000, Train Loss: 1.2306, Train Accuracy: 0.6975, Val Loss: 1.2976, Val Accuracy: 0.6071
Epoch 3903/10000, Train Loss: 1.2235, Train Accuracy: 0.6964, Val Loss: 1.2975, Val Accuracy: 0.6071
Epoch 3904/10000, Train Loss: 1.2330, Train Accuracy: 0.6864, Val Loss: 1.2974, Val Accuracy: 0.6071
Epoch 3905/10000, Train Loss: 1.2353, Train Accuracy: 0.6819, Val Loss: 1.2975, Val Accuracy: 0.6027
Epoch 3906/10000, Train Loss: 1.2220, Train Accuracy: 0.6964, Val Loss: 1.2976, Val Accuracy: 0.6027
Epoch 3907/10000, Train Loss: 1.2273, Train Accuracy: 0.6942, Val Loss: 1.2974, Val Accuracy: 0.6027
Epoch 3908/10000, Train Loss: 1.2102, Train Accuracy: 0.7176, Val Loss: 1.2973, Val Accuracy: 0.6027
Epoch 3909/10000, Train Loss: 1.2243, Train Accuracy: 0.7109, Val Loss: 1.2973, Val Accuracy: 0.6071
Epoch 3910/10000, Train Loss: 1.2247, Train Accuracy: 0.6964, Val Loss: 1.2972, Val Accuracy: 0.6071
Epoch 3911/10000, Train Loss: 1.2337, Train Accuracy: 0.6942, Val Loss: 1.2970, Val Accuracy: 0.6027
Epoch 3912/10000, Train Loss: 1.2301, Train Accuracy: 0.6819, Val Loss: 1.2971, Val Accuracy: 0.6027
Epoch 3913/10000, Train Loss: 1.2238, Train Accuracy: 0.6998, Val Loss: 1.2970, Val Accuracy: 0.6027
Epoch 3914/10000, Train Loss: 1.2291, Train Accuracy: 0.6886, Val Loss: 1.2969, Val Accuracy: 0.6027
Epoch 3915/10000, Train Loss: 1.2235, Train Accuracy: 0.6964, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3916/10000, Train Loss: 1.2301, Train Accuracy: 0.6998, Val Loss: 1.2969, Val Accuracy: 0.6027
Epoch 3917/10000, Train Loss: 1.2215, Train Accuracy: 0.7042, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3918/10000, Train Loss: 1.2207, Train Accuracy: 0.7054, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3919/10000, Train Loss: 1.2300, Train Accuracy: 0.6842, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3920/10000, Train Loss: 1.2293, Train Accuracy: 0.6830, Val Loss: 1.2967, Val Accuracy: 0.6027
Epoch 3921/10000, Train Loss: 1.2353, Train Accuracy: 0.6864, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3922/10000, Train Loss: 1.2244, Train Accuracy: 0.7109, Val Loss: 1.2968, Val Accuracy: 0.6027
Epoch 3923/10000, Train Loss: 1.2280, Train Accuracy: 0.6853, Val Loss: 1.2967, Val Accuracy: 0.6027
Epoch 3924/10000, Train Loss: 1.2264, Train Accuracy: 0.7031, Val Loss: 1.2966, Val Accuracy: 0.6027
Epoch 3925/10000, Train Loss: 1.2369, Train Accuracy: 0.6808, Val Loss: 1.2966, Val Accuracy: 0.6071
Epoch 3926/10000, Train Loss: 1.2243, Train Accuracy: 0.7065, Val Loss: 1.2965, Val Accuracy: 0.6027
Epoch 3927/10000, Train Loss: 1.2359, Train Accuracy: 0.6853, Val Loss: 1.2965, Val Accuracy: 0.6027
Epoch 3928/10000, Train Loss: 1.2268, Train Accuracy: 0.6953, Val Loss: 1.2965, Val Accuracy: 0.6027
Epoch 3929/10000, Train Loss: 1.2335, Train Accuracy: 0.6897, Val Loss: 1.2963, Val Accuracy: 0.6071
Epoch 3930/10000, Train Loss: 1.2314, Train Accuracy: 0.6864, Val Loss: 1.2963, Val Accuracy: 0.6071
Epoch 3931/10000, Train Loss: 1.2266, Train Accuracy: 0.6964, Val Loss: 1.2962, Val Accuracy: 0.6071
Epoch 3932/10000, Train Loss: 1.2212, Train Accuracy: 0.7065, Val Loss: 1.2961, Val Accuracy: 0.6071
Epoch 3933/10000, Train Loss: 1.2285, Train Accuracy: 0.6942, Val Loss: 1.2961, Val Accuracy: 0.6071
Epoch 3934/10000, Train Loss: 1.2281, Train Accuracy: 0.6931, Val Loss: 1.2961, Val Accuracy: 0.6027
Epoch 3935/10000, Train Loss: 1.2264, Train Accuracy: 0.7065, Val Loss: 1.2961, Val Accuracy: 0.6027
Epoch 3936/10000, Train Loss: 1.2266, Train Accuracy: 0.6842, Val Loss: 1.2961, Val Accuracy: 0.6071
Epoch 3937/10000, Train Loss: 1.2228, Train Accuracy: 0.6875, Val Loss: 1.2962, Val Accuracy: 0.6027
Epoch 3938/10000, Train Loss: 1.2352, Train Accuracy: 0.6853, Val Loss: 1.2961, Val Accuracy: 0.6116
Epoch 3939/10000, Train Loss: 1.2265, Train Accuracy: 0.7031, Val Loss: 1.2961, Val Accuracy: 0.6116
Epoch 3940/10000, Train Loss: 1.2229, Train Accuracy: 0.7042, Val Loss: 1.2961, Val Accuracy: 0.6116
Epoch 3941/10000, Train Loss: 1.2291, Train Accuracy: 0.6953, Val Loss: 1.2960, Val Accuracy: 0.6116
Epoch 3942/10000, Train Loss: 1.2200, Train Accuracy: 0.6975, Val Loss: 1.2959, Val Accuracy: 0.6071
Epoch 3943/10000, Train Loss: 1.2273, Train Accuracy: 0.6987, Val Loss: 1.2959, Val Accuracy: 0.6071
Epoch 3944/10000, Train Loss: 1.2316, Train Accuracy: 0.6931, Val Loss: 1.2958, Val Accuracy: 0.6027
Epoch 3945/10000, Train Loss: 1.2243, Train Accuracy: 0.6953, Val Loss: 1.2958, Val Accuracy: 0.6027
Epoch 3946/10000, Train Loss: 1.2367, Train Accuracy: 0.6908, Val Loss: 1.2957, Val Accuracy: 0.6071
Epoch 3947/10000, Train Loss: 1.2274, Train Accuracy: 0.6942, Val Loss: 1.2956, Val Accuracy: 0.6027
Epoch 3948/10000, Train Loss: 1.2268, Train Accuracy: 0.7009, Val Loss: 1.2956, Val Accuracy: 0.6071
Epoch 3949/10000, Train Loss: 1.2248, Train Accuracy: 0.7109, Val Loss: 1.2955, Val Accuracy: 0.6027
Epoch 3950/10000, Train Loss: 1.2236, Train Accuracy: 0.6953, Val Loss: 1.2955, Val Accuracy: 0.6027
Epoch 3951/10000, Train Loss: 1.2260, Train Accuracy: 0.7054, Val Loss: 1.2954, Val Accuracy: 0.6027
Epoch 3952/10000, Train Loss: 1.2388, Train Accuracy: 0.6786, Val Loss: 1.2953, Val Accuracy: 0.6027
Epoch 3953/10000, Train Loss: 1.2162, Train Accuracy: 0.7065, Val Loss: 1.2953, Val Accuracy: 0.6071
Epoch 3954/10000, Train Loss: 1.2289, Train Accuracy: 0.6842, Val Loss: 1.2954, Val Accuracy: 0.6116
Epoch 3955/10000, Train Loss: 1.2361, Train Accuracy: 0.6752, Val Loss: 1.2953, Val Accuracy: 0.6071
Epoch 3956/10000, Train Loss: 1.2243, Train Accuracy: 0.7020, Val Loss: 1.2952, Val Accuracy: 0.6071
Epoch 3957/10000, Train Loss: 1.2307, Train Accuracy: 0.6920, Val Loss: 1.2951, Val Accuracy: 0.6071
Epoch 3958/10000, Train Loss: 1.2290, Train Accuracy: 0.6842, Val Loss: 1.2950, Val Accuracy: 0.6071
Epoch 3959/10000, Train Loss: 1.2176, Train Accuracy: 0.7121, Val Loss: 1.2951, Val Accuracy: 0.6071
Epoch 3960/10000, Train Loss: 1.2346, Train Accuracy: 0.6886, Val Loss: 1.2949, Val Accuracy: 0.6071
Epoch 3961/10000, Train Loss: 1.2195, Train Accuracy: 0.7109, Val Loss: 1.2948, Val Accuracy: 0.6071
Epoch 3962/10000, Train Loss: 1.2341, Train Accuracy: 0.6763, Val Loss: 1.2948, Val Accuracy: 0.6116
Epoch 3963/10000, Train Loss: 1.2356, Train Accuracy: 0.6830, Val Loss: 1.2946, Val Accuracy: 0.6116
Epoch 3964/10000, Train Loss: 1.2258, Train Accuracy: 0.7009, Val Loss: 1.2945, Val Accuracy: 0.6116
Epoch 3965/10000, Train Loss: 1.2135, Train Accuracy: 0.7121, Val Loss: 1.2944, Val Accuracy: 0.6116
Epoch 3966/10000, Train Loss: 1.2158, Train Accuracy: 0.7076, Val Loss: 1.2943, Val Accuracy: 0.6116
Epoch 3967/10000, Train Loss: 1.2185, Train Accuracy: 0.7087, Val Loss: 1.2943, Val Accuracy: 0.6116
Epoch 3968/10000, Train Loss: 1.2339, Train Accuracy: 0.6886, Val Loss: 1.2943, Val Accuracy: 0.6116
Epoch 3969/10000, Train Loss: 1.2301, Train Accuracy: 0.6953, Val Loss: 1.2944, Val Accuracy: 0.6116
Epoch 3970/10000, Train Loss: 1.2298, Train Accuracy: 0.6908, Val Loss: 1.2943, Val Accuracy: 0.6071
Epoch 3971/10000, Train Loss: 1.2237, Train Accuracy: 0.6987, Val Loss: 1.2942, Val Accuracy: 0.6116
Epoch 3972/10000, Train Loss: 1.2153, Train Accuracy: 0.6975, Val Loss: 1.2941, Val Accuracy: 0.6116
Epoch 3973/10000, Train Loss: 1.2289, Train Accuracy: 0.6897, Val Loss: 1.2941, Val Accuracy: 0.6116
Epoch 3974/10000, Train Loss: 1.2190, Train Accuracy: 0.7042, Val Loss: 1.2940, Val Accuracy: 0.6116
Epoch 3975/10000, Train Loss: 1.2161, Train Accuracy: 0.7065, Val Loss: 1.2940, Val Accuracy: 0.6116
Epoch 3976/10000, Train Loss: 1.2286, Train Accuracy: 0.6886, Val Loss: 1.2939, Val Accuracy: 0.6116
Epoch 3977/10000, Train Loss: 1.2260, Train Accuracy: 0.7031, Val Loss: 1.2938, Val Accuracy: 0.6116
Epoch 3978/10000, Train Loss: 1.2137, Train Accuracy: 0.7065, Val Loss: 1.2939, Val Accuracy: 0.6116
Epoch 3979/10000, Train Loss: 1.2235, Train Accuracy: 0.7054, Val Loss: 1.2938, Val Accuracy: 0.6116
Epoch 3980/10000, Train Loss: 1.2328, Train Accuracy: 0.6752, Val Loss: 1.2938, Val Accuracy: 0.6116
Epoch 3981/10000, Train Loss: 1.2207, Train Accuracy: 0.7076, Val Loss: 1.2937, Val Accuracy: 0.6116
Epoch 3982/10000, Train Loss: 1.2173, Train Accuracy: 0.6953, Val Loss: 1.2937, Val Accuracy: 0.6071
Epoch 3983/10000, Train Loss: 1.2343, Train Accuracy: 0.6864, Val Loss: 1.2936, Val Accuracy: 0.6116
Epoch 3984/10000, Train Loss: 1.2333, Train Accuracy: 0.6920, Val Loss: 1.2935, Val Accuracy: 0.6116
Epoch 3985/10000, Train Loss: 1.2223, Train Accuracy: 0.6975, Val Loss: 1.2935, Val Accuracy: 0.6071
Epoch 3986/10000, Train Loss: 1.2136, Train Accuracy: 0.7098, Val Loss: 1.2935, Val Accuracy: 0.6071
Epoch 3987/10000, Train Loss: 1.2137, Train Accuracy: 0.7065, Val Loss: 1.2935, Val Accuracy: 0.6071
Epoch 3988/10000, Train Loss: 1.2155, Train Accuracy: 0.7143, Val Loss: 1.2934, Val Accuracy: 0.6116
Epoch 3989/10000, Train Loss: 1.2164, Train Accuracy: 0.7154, Val Loss: 1.2934, Val Accuracy: 0.6071
Epoch 3990/10000, Train Loss: 1.2203, Train Accuracy: 0.6987, Val Loss: 1.2933, Val Accuracy: 0.6071
Epoch 3991/10000, Train Loss: 1.2177, Train Accuracy: 0.7031, Val Loss: 1.2932, Val Accuracy: 0.6071
Epoch 3992/10000, Train Loss: 1.2239, Train Accuracy: 0.6886, Val Loss: 1.2932, Val Accuracy: 0.6071
Epoch 3993/10000, Train Loss: 1.2270, Train Accuracy: 0.6897, Val Loss: 1.2931, Val Accuracy: 0.6071
Epoch 3994/10000, Train Loss: 1.2191, Train Accuracy: 0.7076, Val Loss: 1.2930, Val Accuracy: 0.6071
Epoch 3995/10000, Train Loss: 1.2210, Train Accuracy: 0.7065, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 3996/10000, Train Loss: 1.2335, Train Accuracy: 0.6864, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 3997/10000, Train Loss: 1.2272, Train Accuracy: 0.7031, Val Loss: 1.2927, Val Accuracy: 0.6071
Epoch 3998/10000, Train Loss: 1.2210, Train Accuracy: 0.6998, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 3999/10000, Train Loss: 1.2237, Train Accuracy: 0.7042, Val Loss: 1.2927, Val Accuracy: 0.6071
Epoch 4000/10000, Train Loss: 1.2156, Train Accuracy: 0.7076, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 4001/10000, Train Loss: 1.2223, Train Accuracy: 0.6908, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 4002/10000, Train Loss: 1.2155, Train Accuracy: 0.7165, Val Loss: 1.2929, Val Accuracy: 0.6071
Epoch 4003/10000, Train Loss: 1.2317, Train Accuracy: 0.6830, Val Loss: 1.2928, Val Accuracy: 0.6071
Epoch 4004/10000, Train Loss: 1.2288, Train Accuracy: 0.6853, Val Loss: 1.2927, Val Accuracy: 0.6071
Epoch 4005/10000, Train Loss: 1.2131, Train Accuracy: 0.7154, Val Loss: 1.2925, Val Accuracy: 0.6071
Epoch 4006/10000, Train Loss: 1.2237, Train Accuracy: 0.6920, Val Loss: 1.2924, Val Accuracy: 0.6071
Epoch 4007/10000, Train Loss: 1.2196, Train Accuracy: 0.7054, Val Loss: 1.2924, Val Accuracy: 0.6071
Epoch 4008/10000, Train Loss: 1.2348, Train Accuracy: 0.6775, Val Loss: 1.2924, Val Accuracy: 0.6071
Epoch 4009/10000, Train Loss: 1.2378, Train Accuracy: 0.6685, Val Loss: 1.2925, Val Accuracy: 0.6071
Epoch 4010/10000, Train Loss: 1.2068, Train Accuracy: 0.7188, Val Loss: 1.2922, Val Accuracy: 0.6071
Epoch 4011/10000, Train Loss: 1.2233, Train Accuracy: 0.6920, Val Loss: 1.2922, Val Accuracy: 0.6071
Epoch 4012/10000, Train Loss: 1.2323, Train Accuracy: 0.6853, Val Loss: 1.2923, Val Accuracy: 0.6071
Epoch 4013/10000, Train Loss: 1.2267, Train Accuracy: 0.6819, Val Loss: 1.2923, Val Accuracy: 0.6071
Epoch 4014/10000, Train Loss: 1.2198, Train Accuracy: 0.6964, Val Loss: 1.2922, Val Accuracy: 0.6071
Epoch 4015/10000, Train Loss: 1.2200, Train Accuracy: 0.7065, Val Loss: 1.2921, Val Accuracy: 0.6116
Epoch 4016/10000, Train Loss: 1.2055, Train Accuracy: 0.7199, Val Loss: 1.2920, Val Accuracy: 0.6116
Epoch 4017/10000, Train Loss: 1.2331, Train Accuracy: 0.6808, Val Loss: 1.2919, Val Accuracy: 0.6161
Epoch 4018/10000, Train Loss: 1.2264, Train Accuracy: 0.6819, Val Loss: 1.2919, Val Accuracy: 0.6116
Epoch 4019/10000, Train Loss: 1.2274, Train Accuracy: 0.6830, Val Loss: 1.2918, Val Accuracy: 0.6116
Epoch 4020/10000, Train Loss: 1.2284, Train Accuracy: 0.6875, Val Loss: 1.2918, Val Accuracy: 0.6116
Epoch 4021/10000, Train Loss: 1.2204, Train Accuracy: 0.6964, Val Loss: 1.2917, Val Accuracy: 0.6116
Epoch 4022/10000, Train Loss: 1.2191, Train Accuracy: 0.7020, Val Loss: 1.2917, Val Accuracy: 0.6116
Epoch 4023/10000, Train Loss: 1.2302, Train Accuracy: 0.6931, Val Loss: 1.2917, Val Accuracy: 0.6116
Epoch 4024/10000, Train Loss: 1.2226, Train Accuracy: 0.6942, Val Loss: 1.2916, Val Accuracy: 0.6116
Epoch 4025/10000, Train Loss: 1.2186, Train Accuracy: 0.7042, Val Loss: 1.2915, Val Accuracy: 0.6116
Epoch 4026/10000, Train Loss: 1.2162, Train Accuracy: 0.7009, Val Loss: 1.2915, Val Accuracy: 0.6116
Epoch 4027/10000, Train Loss: 1.2216, Train Accuracy: 0.7065, Val Loss: 1.2916, Val Accuracy: 0.6071
Epoch 4028/10000, Train Loss: 1.2053, Train Accuracy: 0.7154, Val Loss: 1.2915, Val Accuracy: 0.6116
Epoch 4029/10000, Train Loss: 1.2265, Train Accuracy: 0.6998, Val Loss: 1.2914, Val Accuracy: 0.6071
Epoch 4030/10000, Train Loss: 1.2159, Train Accuracy: 0.7042, Val Loss: 1.2913, Val Accuracy: 0.6071
Epoch 4031/10000, Train Loss: 1.2228, Train Accuracy: 0.7020, Val Loss: 1.2914, Val Accuracy: 0.6071
Epoch 4032/10000, Train Loss: 1.2286, Train Accuracy: 0.6875, Val Loss: 1.2914, Val Accuracy: 0.6116
Epoch 4033/10000, Train Loss: 1.2183, Train Accuracy: 0.7065, Val Loss: 1.2913, Val Accuracy: 0.6071
Epoch 4034/10000, Train Loss: 1.2111, Train Accuracy: 0.7065, Val Loss: 1.2914, Val Accuracy: 0.6071
Epoch 4035/10000, Train Loss: 1.2199, Train Accuracy: 0.7076, Val Loss: 1.2912, Val Accuracy: 0.6116
Epoch 4036/10000, Train Loss: 1.2259, Train Accuracy: 0.6964, Val Loss: 1.2911, Val Accuracy: 0.6116
Epoch 4037/10000, Train Loss: 1.2287, Train Accuracy: 0.6920, Val Loss: 1.2910, Val Accuracy: 0.6161
Epoch 4038/10000, Train Loss: 1.2302, Train Accuracy: 0.6886, Val Loss: 1.2909, Val Accuracy: 0.6161
Epoch 4039/10000, Train Loss: 1.2052, Train Accuracy: 0.7199, Val Loss: 1.2909, Val Accuracy: 0.6161
Epoch 4040/10000, Train Loss: 1.2129, Train Accuracy: 0.7176, Val Loss: 1.2909, Val Accuracy: 0.6161
Epoch 4041/10000, Train Loss: 1.2010, Train Accuracy: 0.7210, Val Loss: 1.2908, Val Accuracy: 0.6161
Epoch 4042/10000, Train Loss: 1.2189, Train Accuracy: 0.6964, Val Loss: 1.2908, Val Accuracy: 0.6161
Epoch 4043/10000, Train Loss: 1.2176, Train Accuracy: 0.7031, Val Loss: 1.2906, Val Accuracy: 0.6161
Epoch 4044/10000, Train Loss: 1.2101, Train Accuracy: 0.7188, Val Loss: 1.2906, Val Accuracy: 0.6161
Epoch 4045/10000, Train Loss: 1.2294, Train Accuracy: 0.6897, Val Loss: 1.2905, Val Accuracy: 0.6161
Epoch 4046/10000, Train Loss: 1.2082, Train Accuracy: 0.7221, Val Loss: 1.2904, Val Accuracy: 0.6161
Epoch 4047/10000, Train Loss: 1.2132, Train Accuracy: 0.7054, Val Loss: 1.2903, Val Accuracy: 0.6161
Epoch 4048/10000, Train Loss: 1.2184, Train Accuracy: 0.7076, Val Loss: 1.2904, Val Accuracy: 0.6161
Epoch 4049/10000, Train Loss: 1.2158, Train Accuracy: 0.7087, Val Loss: 1.2904, Val Accuracy: 0.6116
Epoch 4050/10000, Train Loss: 1.2204, Train Accuracy: 0.7031, Val Loss: 1.2903, Val Accuracy: 0.6116
Epoch 4051/10000, Train Loss: 1.2265, Train Accuracy: 0.6920, Val Loss: 1.2903, Val Accuracy: 0.6116
Epoch 4052/10000, Train Loss: 1.2141, Train Accuracy: 0.7020, Val Loss: 1.2902, Val Accuracy: 0.6116
Epoch 4053/10000, Train Loss: 1.2170, Train Accuracy: 0.6975, Val Loss: 1.2900, Val Accuracy: 0.6116
Epoch 4054/10000, Train Loss: 1.2244, Train Accuracy: 0.6975, Val Loss: 1.2900, Val Accuracy: 0.6116
Epoch 4055/10000, Train Loss: 1.2102, Train Accuracy: 0.7154, Val Loss: 1.2899, Val Accuracy: 0.6116
Epoch 4056/10000, Train Loss: 1.2099, Train Accuracy: 0.7221, Val Loss: 1.2900, Val Accuracy: 0.6116
Epoch 4057/10000, Train Loss: 1.2104, Train Accuracy: 0.7098, Val Loss: 1.2899, Val Accuracy: 0.6116
Epoch 4058/10000, Train Loss: 1.2059, Train Accuracy: 0.7176, Val Loss: 1.2899, Val Accuracy: 0.6116
Epoch 4059/10000, Train Loss: 1.2143, Train Accuracy: 0.7165, Val Loss: 1.2899, Val Accuracy: 0.6116
Epoch 4060/10000, Train Loss: 1.2109, Train Accuracy: 0.7132, Val Loss: 1.2897, Val Accuracy: 0.6116
Epoch 4061/10000, Train Loss: 1.2070, Train Accuracy: 0.7109, Val Loss: 1.2897, Val Accuracy: 0.6116
Epoch 4062/10000, Train Loss: 1.2212, Train Accuracy: 0.7031, Val Loss: 1.2896, Val Accuracy: 0.6116
Epoch 4063/10000, Train Loss: 1.2174, Train Accuracy: 0.7042, Val Loss: 1.2896, Val Accuracy: 0.6116
Epoch 4064/10000, Train Loss: 1.2224, Train Accuracy: 0.7042, Val Loss: 1.2896, Val Accuracy: 0.6116
Epoch 4065/10000, Train Loss: 1.2070, Train Accuracy: 0.7188, Val Loss: 1.2897, Val Accuracy: 0.6116
Epoch 4066/10000, Train Loss: 1.2225, Train Accuracy: 0.7009, Val Loss: 1.2898, Val Accuracy: 0.6116
Epoch 4067/10000, Train Loss: 1.2178, Train Accuracy: 0.7020, Val Loss: 1.2897, Val Accuracy: 0.6116
Epoch 4068/10000, Train Loss: 1.2154, Train Accuracy: 0.7087, Val Loss: 1.2895, Val Accuracy: 0.6116
Epoch 4069/10000, Train Loss: 1.2158, Train Accuracy: 0.7031, Val Loss: 1.2894, Val Accuracy: 0.6116
Epoch 4070/10000, Train Loss: 1.2284, Train Accuracy: 0.6853, Val Loss: 1.2893, Val Accuracy: 0.6116
Epoch 4071/10000, Train Loss: 1.2089, Train Accuracy: 0.7165, Val Loss: 1.2892, Val Accuracy: 0.6116
Epoch 4072/10000, Train Loss: 1.2240, Train Accuracy: 0.6942, Val Loss: 1.2891, Val Accuracy: 0.6161
Epoch 4073/10000, Train Loss: 1.2216, Train Accuracy: 0.7031, Val Loss: 1.2891, Val Accuracy: 0.6161
Epoch 4074/10000, Train Loss: 1.2160, Train Accuracy: 0.7087, Val Loss: 1.2891, Val Accuracy: 0.6161
Epoch 4075/10000, Train Loss: 1.2139, Train Accuracy: 0.7009, Val Loss: 1.2890, Val Accuracy: 0.6116
Epoch 4076/10000, Train Loss: 1.2076, Train Accuracy: 0.7098, Val Loss: 1.2890, Val Accuracy: 0.6161
Epoch 4077/10000, Train Loss: 1.2193, Train Accuracy: 0.7031, Val Loss: 1.2889, Val Accuracy: 0.6161
Epoch 4078/10000, Train Loss: 1.2116, Train Accuracy: 0.7132, Val Loss: 1.2888, Val Accuracy: 0.6161
Epoch 4079/10000, Train Loss: 1.2102, Train Accuracy: 0.7121, Val Loss: 1.2886, Val Accuracy: 0.6161
Epoch 4080/10000, Train Loss: 1.2262, Train Accuracy: 0.6786, Val Loss: 1.2887, Val Accuracy: 0.6161
Epoch 4081/10000, Train Loss: 1.2108, Train Accuracy: 0.7076, Val Loss: 1.2885, Val Accuracy: 0.6205
Epoch 4082/10000, Train Loss: 1.2134, Train Accuracy: 0.7165, Val Loss: 1.2886, Val Accuracy: 0.6205
Epoch 4083/10000, Train Loss: 1.2229, Train Accuracy: 0.6953, Val Loss: 1.2886, Val Accuracy: 0.6205
Epoch 4084/10000, Train Loss: 1.2217, Train Accuracy: 0.7020, Val Loss: 1.2887, Val Accuracy: 0.6205
Epoch 4085/10000, Train Loss: 1.2165, Train Accuracy: 0.6975, Val Loss: 1.2886, Val Accuracy: 0.6205
Epoch 4086/10000, Train Loss: 1.2266, Train Accuracy: 0.6908, Val Loss: 1.2885, Val Accuracy: 0.6161
Epoch 4087/10000, Train Loss: 1.2082, Train Accuracy: 0.7132, Val Loss: 1.2885, Val Accuracy: 0.6205
Epoch 4088/10000, Train Loss: 1.2191, Train Accuracy: 0.7054, Val Loss: 1.2885, Val Accuracy: 0.6161
Epoch 4089/10000, Train Loss: 1.2133, Train Accuracy: 0.7165, Val Loss: 1.2884, Val Accuracy: 0.6161
Epoch 4090/10000, Train Loss: 1.2128, Train Accuracy: 0.7009, Val Loss: 1.2884, Val Accuracy: 0.6161
Epoch 4091/10000, Train Loss: 1.2256, Train Accuracy: 0.6908, Val Loss: 1.2883, Val Accuracy: 0.6161
Epoch 4092/10000, Train Loss: 1.2146, Train Accuracy: 0.7121, Val Loss: 1.2882, Val Accuracy: 0.6161
Epoch 4093/10000, Train Loss: 1.2154, Train Accuracy: 0.7054, Val Loss: 1.2882, Val Accuracy: 0.6161
Epoch 4094/10000, Train Loss: 1.2082, Train Accuracy: 0.7199, Val Loss: 1.2881, Val Accuracy: 0.6161
Epoch 4095/10000, Train Loss: 1.2002, Train Accuracy: 0.7254, Val Loss: 1.2881, Val Accuracy: 0.6161
Epoch 4096/10000, Train Loss: 1.2131, Train Accuracy: 0.7054, Val Loss: 1.2880, Val Accuracy: 0.6205
Epoch 4097/10000, Train Loss: 1.2139, Train Accuracy: 0.7076, Val Loss: 1.2879, Val Accuracy: 0.6161
Epoch 4098/10000, Train Loss: 1.2183, Train Accuracy: 0.7042, Val Loss: 1.2881, Val Accuracy: 0.6161
Epoch 4099/10000, Train Loss: 1.2180, Train Accuracy: 0.6897, Val Loss: 1.2881, Val Accuracy: 0.6161
Epoch 4100/10000, Train Loss: 1.2132, Train Accuracy: 0.7109, Val Loss: 1.2882, Val Accuracy: 0.6161
Epoch 4101/10000, Train Loss: 1.2278, Train Accuracy: 0.6920, Val Loss: 1.2880, Val Accuracy: 0.6161
Epoch 4102/10000, Train Loss: 1.2101, Train Accuracy: 0.7176, Val Loss: 1.2879, Val Accuracy: 0.6161
Epoch 4103/10000, Train Loss: 1.2125, Train Accuracy: 0.7054, Val Loss: 1.2878, Val Accuracy: 0.6161
Epoch 4104/10000, Train Loss: 1.2106, Train Accuracy: 0.7109, Val Loss: 1.2878, Val Accuracy: 0.6161
Epoch 4105/10000, Train Loss: 1.2073, Train Accuracy: 0.7087, Val Loss: 1.2876, Val Accuracy: 0.6161
Epoch 4106/10000, Train Loss: 1.2223, Train Accuracy: 0.7020, Val Loss: 1.2875, Val Accuracy: 0.6161
Epoch 4107/10000, Train Loss: 1.2226, Train Accuracy: 0.7020, Val Loss: 1.2874, Val Accuracy: 0.6205
Epoch 4108/10000, Train Loss: 1.2141, Train Accuracy: 0.7154, Val Loss: 1.2873, Val Accuracy: 0.6205
Epoch 4109/10000, Train Loss: 1.2176, Train Accuracy: 0.7020, Val Loss: 1.2872, Val Accuracy: 0.6205
Epoch 4110/10000, Train Loss: 1.2121, Train Accuracy: 0.7143, Val Loss: 1.2871, Val Accuracy: 0.6205
Epoch 4111/10000, Train Loss: 1.2061, Train Accuracy: 0.7087, Val Loss: 1.2869, Val Accuracy: 0.6205
Epoch 4112/10000, Train Loss: 1.2041, Train Accuracy: 0.7176, Val Loss: 1.2868, Val Accuracy: 0.6205
Epoch 4113/10000, Train Loss: 1.2030, Train Accuracy: 0.7299, Val Loss: 1.2868, Val Accuracy: 0.6250
Epoch 4114/10000, Train Loss: 1.2110, Train Accuracy: 0.7065, Val Loss: 1.2867, Val Accuracy: 0.6250
Epoch 4115/10000, Train Loss: 1.2328, Train Accuracy: 0.6786, Val Loss: 1.2865, Val Accuracy: 0.6250
Epoch 4116/10000, Train Loss: 1.2094, Train Accuracy: 0.7121, Val Loss: 1.2865, Val Accuracy: 0.6250
Epoch 4117/10000, Train Loss: 1.2229, Train Accuracy: 0.6998, Val Loss: 1.2864, Val Accuracy: 0.6250
Epoch 4118/10000, Train Loss: 1.2192, Train Accuracy: 0.7009, Val Loss: 1.2863, Val Accuracy: 0.6250
Epoch 4119/10000, Train Loss: 1.2143, Train Accuracy: 0.7076, Val Loss: 1.2863, Val Accuracy: 0.6250
Epoch 4120/10000, Train Loss: 1.2104, Train Accuracy: 0.7165, Val Loss: 1.2863, Val Accuracy: 0.6250
Epoch 4121/10000, Train Loss: 1.2072, Train Accuracy: 0.7143, Val Loss: 1.2862, Val Accuracy: 0.6205
Epoch 4122/10000, Train Loss: 1.2103, Train Accuracy: 0.7176, Val Loss: 1.2862, Val Accuracy: 0.6250
Epoch 4123/10000, Train Loss: 1.2055, Train Accuracy: 0.7254, Val Loss: 1.2861, Val Accuracy: 0.6205
Epoch 4124/10000, Train Loss: 1.2157, Train Accuracy: 0.6975, Val Loss: 1.2861, Val Accuracy: 0.6205
Epoch 4125/10000, Train Loss: 1.1987, Train Accuracy: 0.7299, Val Loss: 1.2860, Val Accuracy: 0.6205
Epoch 4126/10000, Train Loss: 1.2137, Train Accuracy: 0.7154, Val Loss: 1.2860, Val Accuracy: 0.6205
Epoch 4127/10000, Train Loss: 1.2181, Train Accuracy: 0.7065, Val Loss: 1.2859, Val Accuracy: 0.6205
Epoch 4128/10000, Train Loss: 1.2144, Train Accuracy: 0.7143, Val Loss: 1.2857, Val Accuracy: 0.6205
Epoch 4129/10000, Train Loss: 1.2080, Train Accuracy: 0.7109, Val Loss: 1.2857, Val Accuracy: 0.6205
Epoch 4130/10000, Train Loss: 1.2216, Train Accuracy: 0.7042, Val Loss: 1.2857, Val Accuracy: 0.6205
Epoch 4131/10000, Train Loss: 1.2016, Train Accuracy: 0.7277, Val Loss: 1.2857, Val Accuracy: 0.6250
Epoch 4132/10000, Train Loss: 1.2196, Train Accuracy: 0.6975, Val Loss: 1.2856, Val Accuracy: 0.6250
Epoch 4133/10000, Train Loss: 1.2139, Train Accuracy: 0.7165, Val Loss: 1.2855, Val Accuracy: 0.6250
Epoch 4134/10000, Train Loss: 1.2036, Train Accuracy: 0.7210, Val Loss: 1.2854, Val Accuracy: 0.6250
Epoch 4135/10000, Train Loss: 1.2236, Train Accuracy: 0.6931, Val Loss: 1.2853, Val Accuracy: 0.6250
Epoch 4136/10000, Train Loss: 1.2134, Train Accuracy: 0.7042, Val Loss: 1.2853, Val Accuracy: 0.6250
Epoch 4137/10000, Train Loss: 1.2040, Train Accuracy: 0.7254, Val Loss: 1.2853, Val Accuracy: 0.6250
Epoch 4138/10000, Train Loss: 1.2162, Train Accuracy: 0.7065, Val Loss: 1.2853, Val Accuracy: 0.6250
Epoch 4139/10000, Train Loss: 1.2162, Train Accuracy: 0.7031, Val Loss: 1.2854, Val Accuracy: 0.6250
Epoch 4140/10000, Train Loss: 1.2160, Train Accuracy: 0.7087, Val Loss: 1.2853, Val Accuracy: 0.6205
Epoch 4141/10000, Train Loss: 1.2152, Train Accuracy: 0.6998, Val Loss: 1.2854, Val Accuracy: 0.6205
Epoch 4142/10000, Train Loss: 1.2219, Train Accuracy: 0.7031, Val Loss: 1.2853, Val Accuracy: 0.6205
Epoch 4143/10000, Train Loss: 1.2233, Train Accuracy: 0.6942, Val Loss: 1.2852, Val Accuracy: 0.6205
Epoch 4144/10000, Train Loss: 1.2197, Train Accuracy: 0.7020, Val Loss: 1.2851, Val Accuracy: 0.6250
Epoch 4145/10000, Train Loss: 1.2033, Train Accuracy: 0.7154, Val Loss: 1.2851, Val Accuracy: 0.6250
Epoch 4146/10000, Train Loss: 1.2176, Train Accuracy: 0.6987, Val Loss: 1.2852, Val Accuracy: 0.6205
Epoch 4147/10000, Train Loss: 1.2175, Train Accuracy: 0.6964, Val Loss: 1.2851, Val Accuracy: 0.6250
Epoch 4148/10000, Train Loss: 1.2038, Train Accuracy: 0.7344, Val Loss: 1.2851, Val Accuracy: 0.6205
Epoch 4149/10000, Train Loss: 1.2173, Train Accuracy: 0.6987, Val Loss: 1.2851, Val Accuracy: 0.6205
Epoch 4150/10000, Train Loss: 1.2067, Train Accuracy: 0.7188, Val Loss: 1.2849, Val Accuracy: 0.6205
Epoch 4151/10000, Train Loss: 1.2129, Train Accuracy: 0.7132, Val Loss: 1.2849, Val Accuracy: 0.6205
Epoch 4152/10000, Train Loss: 1.2068, Train Accuracy: 0.7143, Val Loss: 1.2850, Val Accuracy: 0.6205
Epoch 4153/10000, Train Loss: 1.2126, Train Accuracy: 0.7031, Val Loss: 1.2849, Val Accuracy: 0.6205
Epoch 4154/10000, Train Loss: 1.1981, Train Accuracy: 0.7243, Val Loss: 1.2848, Val Accuracy: 0.6205
Epoch 4155/10000, Train Loss: 1.2093, Train Accuracy: 0.7176, Val Loss: 1.2848, Val Accuracy: 0.6205
Epoch 4156/10000, Train Loss: 1.2171, Train Accuracy: 0.6953, Val Loss: 1.2848, Val Accuracy: 0.6205
Epoch 4157/10000, Train Loss: 1.2173, Train Accuracy: 0.7076, Val Loss: 1.2847, Val Accuracy: 0.6205
Epoch 4158/10000, Train Loss: 1.2156, Train Accuracy: 0.6998, Val Loss: 1.2846, Val Accuracy: 0.6205
Epoch 4159/10000, Train Loss: 1.2021, Train Accuracy: 0.7210, Val Loss: 1.2846, Val Accuracy: 0.6205
Epoch 4160/10000, Train Loss: 1.2188, Train Accuracy: 0.7042, Val Loss: 1.2846, Val Accuracy: 0.6205
Epoch 4161/10000, Train Loss: 1.1986, Train Accuracy: 0.7232, Val Loss: 1.2845, Val Accuracy: 0.6205
Epoch 4162/10000, Train Loss: 1.2147, Train Accuracy: 0.7042, Val Loss: 1.2844, Val Accuracy: 0.6205
Epoch 4163/10000, Train Loss: 1.2194, Train Accuracy: 0.6953, Val Loss: 1.2843, Val Accuracy: 0.6205
Epoch 4164/10000, Train Loss: 1.2051, Train Accuracy: 0.7087, Val Loss: 1.2843, Val Accuracy: 0.6205
Epoch 4165/10000, Train Loss: 1.2124, Train Accuracy: 0.7054, Val Loss: 1.2843, Val Accuracy: 0.6205
Epoch 4166/10000, Train Loss: 1.2159, Train Accuracy: 0.7054, Val Loss: 1.2841, Val Accuracy: 0.6205
Epoch 4167/10000, Train Loss: 1.2061, Train Accuracy: 0.7121, Val Loss: 1.2841, Val Accuracy: 0.6205
Epoch 4168/10000, Train Loss: 1.2118, Train Accuracy: 0.7121, Val Loss: 1.2840, Val Accuracy: 0.6205
Epoch 4169/10000, Train Loss: 1.2152, Train Accuracy: 0.7020, Val Loss: 1.2840, Val Accuracy: 0.6205
Epoch 4170/10000, Train Loss: 1.2191, Train Accuracy: 0.6875, Val Loss: 1.2840, Val Accuracy: 0.6205
Epoch 4171/10000, Train Loss: 1.2113, Train Accuracy: 0.7087, Val Loss: 1.2839, Val Accuracy: 0.6205
Epoch 4172/10000, Train Loss: 1.2035, Train Accuracy: 0.7277, Val Loss: 1.2838, Val Accuracy: 0.6205
Epoch 4173/10000, Train Loss: 1.2137, Train Accuracy: 0.7031, Val Loss: 1.2836, Val Accuracy: 0.6205
Epoch 4174/10000, Train Loss: 1.2172, Train Accuracy: 0.7121, Val Loss: 1.2836, Val Accuracy: 0.6205
Epoch 4175/10000, Train Loss: 1.2168, Train Accuracy: 0.7042, Val Loss: 1.2836, Val Accuracy: 0.6205
Epoch 4176/10000, Train Loss: 1.2111, Train Accuracy: 0.7132, Val Loss: 1.2836, Val Accuracy: 0.6205
Epoch 4177/10000, Train Loss: 1.2122, Train Accuracy: 0.7076, Val Loss: 1.2834, Val Accuracy: 0.6205
Epoch 4178/10000, Train Loss: 1.2171, Train Accuracy: 0.6998, Val Loss: 1.2833, Val Accuracy: 0.6205
Epoch 4179/10000, Train Loss: 1.2047, Train Accuracy: 0.7221, Val Loss: 1.2831, Val Accuracy: 0.6205
Epoch 4180/10000, Train Loss: 1.2048, Train Accuracy: 0.7132, Val Loss: 1.2832, Val Accuracy: 0.6205
Epoch 4181/10000, Train Loss: 1.2162, Train Accuracy: 0.6998, Val Loss: 1.2831, Val Accuracy: 0.6205
Epoch 4182/10000, Train Loss: 1.2144, Train Accuracy: 0.7042, Val Loss: 1.2831, Val Accuracy: 0.6205
Epoch 4183/10000, Train Loss: 1.2023, Train Accuracy: 0.7199, Val Loss: 1.2830, Val Accuracy: 0.6205
Epoch 4184/10000, Train Loss: 1.2003, Train Accuracy: 0.7165, Val Loss: 1.2830, Val Accuracy: 0.6205
Epoch 4185/10000, Train Loss: 1.2073, Train Accuracy: 0.7109, Val Loss: 1.2831, Val Accuracy: 0.6205
Epoch 4186/10000, Train Loss: 1.2130, Train Accuracy: 0.7031, Val Loss: 1.2830, Val Accuracy: 0.6205
Epoch 4187/10000, Train Loss: 1.2159, Train Accuracy: 0.7042, Val Loss: 1.2828, Val Accuracy: 0.6205
Epoch 4188/10000, Train Loss: 1.2046, Train Accuracy: 0.7210, Val Loss: 1.2827, Val Accuracy: 0.6205
Epoch 4189/10000, Train Loss: 1.2153, Train Accuracy: 0.7121, Val Loss: 1.2828, Val Accuracy: 0.6205
Epoch 4190/10000, Train Loss: 1.2139, Train Accuracy: 0.7087, Val Loss: 1.2828, Val Accuracy: 0.6205
Epoch 4191/10000, Train Loss: 1.2058, Train Accuracy: 0.7199, Val Loss: 1.2826, Val Accuracy: 0.6205
Epoch 4192/10000, Train Loss: 1.2012, Train Accuracy: 0.7299, Val Loss: 1.2824, Val Accuracy: 0.6205
Epoch 4193/10000, Train Loss: 1.2127, Train Accuracy: 0.7009, Val Loss: 1.2824, Val Accuracy: 0.6205
Epoch 4194/10000, Train Loss: 1.2053, Train Accuracy: 0.7154, Val Loss: 1.2823, Val Accuracy: 0.6205
Epoch 4195/10000, Train Loss: 1.2132, Train Accuracy: 0.7009, Val Loss: 1.2820, Val Accuracy: 0.6205
Epoch 4196/10000, Train Loss: 1.2083, Train Accuracy: 0.7121, Val Loss: 1.2821, Val Accuracy: 0.6205
Epoch 4197/10000, Train Loss: 1.2130, Train Accuracy: 0.7065, Val Loss: 1.2821, Val Accuracy: 0.6205
Epoch 4198/10000, Train Loss: 1.2168, Train Accuracy: 0.6975, Val Loss: 1.2820, Val Accuracy: 0.6205
Epoch 4199/10000, Train Loss: 1.2130, Train Accuracy: 0.7009, Val Loss: 1.2821, Val Accuracy: 0.6205
Epoch 4200/10000, Train Loss: 1.2117, Train Accuracy: 0.6975, Val Loss: 1.2821, Val Accuracy: 0.6205
Epoch 4201/10000, Train Loss: 1.2096, Train Accuracy: 0.7087, Val Loss: 1.2820, Val Accuracy: 0.6205
Epoch 4202/10000, Train Loss: 1.2040, Train Accuracy: 0.7165, Val Loss: 1.2821, Val Accuracy: 0.6205
Epoch 4203/10000, Train Loss: 1.2039, Train Accuracy: 0.7143, Val Loss: 1.2819, Val Accuracy: 0.6205
Epoch 4204/10000, Train Loss: 1.2099, Train Accuracy: 0.7054, Val Loss: 1.2820, Val Accuracy: 0.6205
Epoch 4205/10000, Train Loss: 1.2060, Train Accuracy: 0.7154, Val Loss: 1.2820, Val Accuracy: 0.6205
Epoch 4206/10000, Train Loss: 1.2024, Train Accuracy: 0.7221, Val Loss: 1.2819, Val Accuracy: 0.6205
Epoch 4207/10000, Train Loss: 1.2184, Train Accuracy: 0.6908, Val Loss: 1.2818, Val Accuracy: 0.6205
Epoch 4208/10000, Train Loss: 1.2020, Train Accuracy: 0.7109, Val Loss: 1.2817, Val Accuracy: 0.6205
Epoch 4209/10000, Train Loss: 1.2015, Train Accuracy: 0.7176, Val Loss: 1.2815, Val Accuracy: 0.6205
Epoch 4210/10000, Train Loss: 1.2185, Train Accuracy: 0.7087, Val Loss: 1.2815, Val Accuracy: 0.6205
Epoch 4211/10000, Train Loss: 1.2053, Train Accuracy: 0.7076, Val Loss: 1.2815, Val Accuracy: 0.6205
Epoch 4212/10000, Train Loss: 1.2059, Train Accuracy: 0.7154, Val Loss: 1.2814, Val Accuracy: 0.6205
Epoch 4213/10000, Train Loss: 1.2172, Train Accuracy: 0.6987, Val Loss: 1.2815, Val Accuracy: 0.6250
Epoch 4214/10000, Train Loss: 1.2113, Train Accuracy: 0.7165, Val Loss: 1.2811, Val Accuracy: 0.6250
Epoch 4215/10000, Train Loss: 1.2052, Train Accuracy: 0.7199, Val Loss: 1.2810, Val Accuracy: 0.6250
Epoch 4216/10000, Train Loss: 1.2027, Train Accuracy: 0.7143, Val Loss: 1.2809, Val Accuracy: 0.6250
Epoch 4217/10000, Train Loss: 1.2071, Train Accuracy: 0.7143, Val Loss: 1.2809, Val Accuracy: 0.6250
Epoch 4218/10000, Train Loss: 1.2000, Train Accuracy: 0.7266, Val Loss: 1.2808, Val Accuracy: 0.6250
Epoch 4219/10000, Train Loss: 1.2117, Train Accuracy: 0.7031, Val Loss: 1.2807, Val Accuracy: 0.6250
Epoch 4220/10000, Train Loss: 1.2103, Train Accuracy: 0.7054, Val Loss: 1.2807, Val Accuracy: 0.6250
Epoch 4221/10000, Train Loss: 1.2156, Train Accuracy: 0.7031, Val Loss: 1.2807, Val Accuracy: 0.6250
Epoch 4222/10000, Train Loss: 1.2083, Train Accuracy: 0.7109, Val Loss: 1.2808, Val Accuracy: 0.6250
Epoch 4223/10000, Train Loss: 1.2158, Train Accuracy: 0.6964, Val Loss: 1.2808, Val Accuracy: 0.6250
Epoch 4224/10000, Train Loss: 1.2077, Train Accuracy: 0.7165, Val Loss: 1.2808, Val Accuracy: 0.6250
Epoch 4225/10000, Train Loss: 1.2128, Train Accuracy: 0.7042, Val Loss: 1.2806, Val Accuracy: 0.6250
Epoch 4226/10000, Train Loss: 1.2030, Train Accuracy: 0.7188, Val Loss: 1.2804, Val Accuracy: 0.6250
Epoch 4227/10000, Train Loss: 1.1991, Train Accuracy: 0.7221, Val Loss: 1.2804, Val Accuracy: 0.6250
Epoch 4228/10000, Train Loss: 1.2118, Train Accuracy: 0.7143, Val Loss: 1.2804, Val Accuracy: 0.6250
Epoch 4229/10000, Train Loss: 1.1998, Train Accuracy: 0.7333, Val Loss: 1.2804, Val Accuracy: 0.6250
Epoch 4230/10000, Train Loss: 1.2012, Train Accuracy: 0.7154, Val Loss: 1.2802, Val Accuracy: 0.6250
Epoch 4231/10000, Train Loss: 1.1995, Train Accuracy: 0.7277, Val Loss: 1.2801, Val Accuracy: 0.6250
Epoch 4232/10000, Train Loss: 1.2066, Train Accuracy: 0.7087, Val Loss: 1.2803, Val Accuracy: 0.6250
Epoch 4233/10000, Train Loss: 1.2079, Train Accuracy: 0.7132, Val Loss: 1.2802, Val Accuracy: 0.6250
Epoch 4234/10000, Train Loss: 1.2073, Train Accuracy: 0.7221, Val Loss: 1.2802, Val Accuracy: 0.6250
Epoch 4235/10000, Train Loss: 1.2053, Train Accuracy: 0.7098, Val Loss: 1.2803, Val Accuracy: 0.6250
Epoch 4236/10000, Train Loss: 1.2084, Train Accuracy: 0.7065, Val Loss: 1.2803, Val Accuracy: 0.6250
Epoch 4237/10000, Train Loss: 1.2020, Train Accuracy: 0.7210, Val Loss: 1.2801, Val Accuracy: 0.6250
Epoch 4238/10000, Train Loss: 1.2109, Train Accuracy: 0.7132, Val Loss: 1.2800, Val Accuracy: 0.6250
Epoch 4239/10000, Train Loss: 1.2178, Train Accuracy: 0.7087, Val Loss: 1.2800, Val Accuracy: 0.6250
Epoch 4240/10000, Train Loss: 1.2025, Train Accuracy: 0.7165, Val Loss: 1.2800, Val Accuracy: 0.6250
Epoch 4241/10000, Train Loss: 1.2110, Train Accuracy: 0.6920, Val Loss: 1.2799, Val Accuracy: 0.6250
Epoch 4242/10000, Train Loss: 1.2100, Train Accuracy: 0.6998, Val Loss: 1.2798, Val Accuracy: 0.6250
Epoch 4243/10000, Train Loss: 1.2071, Train Accuracy: 0.7109, Val Loss: 1.2797, Val Accuracy: 0.6250
Epoch 4244/10000, Train Loss: 1.2007, Train Accuracy: 0.7176, Val Loss: 1.2796, Val Accuracy: 0.6250
Epoch 4245/10000, Train Loss: 1.2058, Train Accuracy: 0.7076, Val Loss: 1.2796, Val Accuracy: 0.6250
Epoch 4246/10000, Train Loss: 1.2098, Train Accuracy: 0.7176, Val Loss: 1.2795, Val Accuracy: 0.6250
Epoch 4247/10000, Train Loss: 1.2045, Train Accuracy: 0.7165, Val Loss: 1.2794, Val Accuracy: 0.6250
Epoch 4248/10000, Train Loss: 1.2115, Train Accuracy: 0.7076, Val Loss: 1.2793, Val Accuracy: 0.6250
Epoch 4249/10000, Train Loss: 1.2163, Train Accuracy: 0.7042, Val Loss: 1.2791, Val Accuracy: 0.6250
Epoch 4250/10000, Train Loss: 1.2068, Train Accuracy: 0.7109, Val Loss: 1.2790, Val Accuracy: 0.6250
Epoch 4251/10000, Train Loss: 1.2003, Train Accuracy: 0.7321, Val Loss: 1.2789, Val Accuracy: 0.6250
Epoch 4252/10000, Train Loss: 1.2054, Train Accuracy: 0.7109, Val Loss: 1.2790, Val Accuracy: 0.6250
Epoch 4253/10000, Train Loss: 1.2046, Train Accuracy: 0.7087, Val Loss: 1.2789, Val Accuracy: 0.6250
Epoch 4254/10000, Train Loss: 1.2167, Train Accuracy: 0.6975, Val Loss: 1.2788, Val Accuracy: 0.6250
Epoch 4255/10000, Train Loss: 1.1991, Train Accuracy: 0.7243, Val Loss: 1.2789, Val Accuracy: 0.6250
Epoch 4256/10000, Train Loss: 1.2075, Train Accuracy: 0.7076, Val Loss: 1.2788, Val Accuracy: 0.6250
Epoch 4257/10000, Train Loss: 1.2142, Train Accuracy: 0.7109, Val Loss: 1.2787, Val Accuracy: 0.6250
Epoch 4258/10000, Train Loss: 1.2071, Train Accuracy: 0.7121, Val Loss: 1.2786, Val Accuracy: 0.6250
Epoch 4259/10000, Train Loss: 1.2032, Train Accuracy: 0.7277, Val Loss: 1.2785, Val Accuracy: 0.6250
Epoch 4260/10000, Train Loss: 1.2045, Train Accuracy: 0.7176, Val Loss: 1.2784, Val Accuracy: 0.6250
Epoch 4261/10000, Train Loss: 1.2093, Train Accuracy: 0.7176, Val Loss: 1.2784, Val Accuracy: 0.6250
Epoch 4262/10000, Train Loss: 1.1999, Train Accuracy: 0.7143, Val Loss: 1.2783, Val Accuracy: 0.6250
Epoch 4263/10000, Train Loss: 1.2099, Train Accuracy: 0.7143, Val Loss: 1.2784, Val Accuracy: 0.6250
Epoch 4264/10000, Train Loss: 1.1991, Train Accuracy: 0.7221, Val Loss: 1.2785, Val Accuracy: 0.6250
Epoch 4265/10000, Train Loss: 1.1952, Train Accuracy: 0.7299, Val Loss: 1.2785, Val Accuracy: 0.6250
Epoch 4266/10000, Train Loss: 1.1892, Train Accuracy: 0.7288, Val Loss: 1.2784, Val Accuracy: 0.6250
Epoch 4267/10000, Train Loss: 1.1929, Train Accuracy: 0.7310, Val Loss: 1.2783, Val Accuracy: 0.6250
Epoch 4268/10000, Train Loss: 1.2050, Train Accuracy: 0.7109, Val Loss: 1.2784, Val Accuracy: 0.6250
Epoch 4269/10000, Train Loss: 1.2048, Train Accuracy: 0.7254, Val Loss: 1.2783, Val Accuracy: 0.6250
Epoch 4270/10000, Train Loss: 1.2015, Train Accuracy: 0.7087, Val Loss: 1.2782, Val Accuracy: 0.6250
Epoch 4271/10000, Train Loss: 1.1962, Train Accuracy: 0.7232, Val Loss: 1.2781, Val Accuracy: 0.6250
Epoch 4272/10000, Train Loss: 1.2144, Train Accuracy: 0.6998, Val Loss: 1.2781, Val Accuracy: 0.6250
Epoch 4273/10000, Train Loss: 1.2021, Train Accuracy: 0.7176, Val Loss: 1.2780, Val Accuracy: 0.6250
Epoch 4274/10000, Train Loss: 1.2111, Train Accuracy: 0.7009, Val Loss: 1.2779, Val Accuracy: 0.6250
Epoch 4275/10000, Train Loss: 1.2018, Train Accuracy: 0.7165, Val Loss: 1.2779, Val Accuracy: 0.6250
Epoch 4276/10000, Train Loss: 1.2065, Train Accuracy: 0.7199, Val Loss: 1.2778, Val Accuracy: 0.6250
Epoch 4277/10000, Train Loss: 1.2041, Train Accuracy: 0.7176, Val Loss: 1.2777, Val Accuracy: 0.6250
Epoch 4278/10000, Train Loss: 1.1997, Train Accuracy: 0.7254, Val Loss: 1.2776, Val Accuracy: 0.6250
Epoch 4279/10000, Train Loss: 1.2038, Train Accuracy: 0.7221, Val Loss: 1.2776, Val Accuracy: 0.6250
Epoch 4280/10000, Train Loss: 1.2138, Train Accuracy: 0.6975, Val Loss: 1.2776, Val Accuracy: 0.6250
Epoch 4281/10000, Train Loss: 1.2130, Train Accuracy: 0.7054, Val Loss: 1.2776, Val Accuracy: 0.6250
Epoch 4282/10000, Train Loss: 1.1928, Train Accuracy: 0.7355, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4283/10000, Train Loss: 1.2112, Train Accuracy: 0.7087, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4284/10000, Train Loss: 1.1995, Train Accuracy: 0.7199, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4285/10000, Train Loss: 1.1940, Train Accuracy: 0.7388, Val Loss: 1.2773, Val Accuracy: 0.6250
Epoch 4286/10000, Train Loss: 1.2063, Train Accuracy: 0.7165, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4287/10000, Train Loss: 1.1931, Train Accuracy: 0.7277, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4288/10000, Train Loss: 1.2002, Train Accuracy: 0.7109, Val Loss: 1.2774, Val Accuracy: 0.6250
Epoch 4289/10000, Train Loss: 1.2095, Train Accuracy: 0.7042, Val Loss: 1.2772, Val Accuracy: 0.6250
Epoch 4290/10000, Train Loss: 1.1963, Train Accuracy: 0.7165, Val Loss: 1.2772, Val Accuracy: 0.6250
Epoch 4291/10000, Train Loss: 1.2063, Train Accuracy: 0.7076, Val Loss: 1.2770, Val Accuracy: 0.6250
Epoch 4292/10000, Train Loss: 1.2080, Train Accuracy: 0.7188, Val Loss: 1.2771, Val Accuracy: 0.6250
Epoch 4293/10000, Train Loss: 1.1995, Train Accuracy: 0.7188, Val Loss: 1.2769, Val Accuracy: 0.6250
Epoch 4294/10000, Train Loss: 1.1970, Train Accuracy: 0.7210, Val Loss: 1.2768, Val Accuracy: 0.6250
Epoch 4295/10000, Train Loss: 1.1975, Train Accuracy: 0.7333, Val Loss: 1.2768, Val Accuracy: 0.6250
Epoch 4296/10000, Train Loss: 1.2131, Train Accuracy: 0.6975, Val Loss: 1.2767, Val Accuracy: 0.6250
Epoch 4297/10000, Train Loss: 1.1946, Train Accuracy: 0.7266, Val Loss: 1.2767, Val Accuracy: 0.6250
Epoch 4298/10000, Train Loss: 1.2014, Train Accuracy: 0.7143, Val Loss: 1.2767, Val Accuracy: 0.6250
Epoch 4299/10000, Train Loss: 1.1893, Train Accuracy: 0.7277, Val Loss: 1.2767, Val Accuracy: 0.6250
Epoch 4300/10000, Train Loss: 1.2079, Train Accuracy: 0.7098, Val Loss: 1.2765, Val Accuracy: 0.6250
Epoch 4301/10000, Train Loss: 1.2195, Train Accuracy: 0.6942, Val Loss: 1.2765, Val Accuracy: 0.6250
Epoch 4302/10000, Train Loss: 1.2088, Train Accuracy: 0.7109, Val Loss: 1.2766, Val Accuracy: 0.6250
Epoch 4303/10000, Train Loss: 1.1898, Train Accuracy: 0.7254, Val Loss: 1.2766, Val Accuracy: 0.6250
Epoch 4304/10000, Train Loss: 1.2087, Train Accuracy: 0.7109, Val Loss: 1.2765, Val Accuracy: 0.6250
Epoch 4305/10000, Train Loss: 1.1954, Train Accuracy: 0.7232, Val Loss: 1.2764, Val Accuracy: 0.6250
Epoch 4306/10000, Train Loss: 1.1974, Train Accuracy: 0.7288, Val Loss: 1.2764, Val Accuracy: 0.6250
Epoch 4307/10000, Train Loss: 1.2002, Train Accuracy: 0.7221, Val Loss: 1.2764, Val Accuracy: 0.6295
Epoch 4308/10000, Train Loss: 1.1899, Train Accuracy: 0.7333, Val Loss: 1.2765, Val Accuracy: 0.6295
Epoch 4309/10000, Train Loss: 1.1952, Train Accuracy: 0.7232, Val Loss: 1.2765, Val Accuracy: 0.6295
Epoch 4310/10000, Train Loss: 1.2064, Train Accuracy: 0.7143, Val Loss: 1.2764, Val Accuracy: 0.6250
Epoch 4311/10000, Train Loss: 1.2010, Train Accuracy: 0.7232, Val Loss: 1.2763, Val Accuracy: 0.6250
Epoch 4312/10000, Train Loss: 1.2087, Train Accuracy: 0.7065, Val Loss: 1.2762, Val Accuracy: 0.6250
Epoch 4313/10000, Train Loss: 1.1935, Train Accuracy: 0.7188, Val Loss: 1.2762, Val Accuracy: 0.6295
Epoch 4314/10000, Train Loss: 1.1948, Train Accuracy: 0.7277, Val Loss: 1.2762, Val Accuracy: 0.6295
Epoch 4315/10000, Train Loss: 1.1917, Train Accuracy: 0.7288, Val Loss: 1.2761, Val Accuracy: 0.6250
Epoch 4316/10000, Train Loss: 1.2004, Train Accuracy: 0.7210, Val Loss: 1.2761, Val Accuracy: 0.6295
Epoch 4317/10000, Train Loss: 1.2084, Train Accuracy: 0.7098, Val Loss: 1.2760, Val Accuracy: 0.6295
Epoch 4318/10000, Train Loss: 1.1933, Train Accuracy: 0.7277, Val Loss: 1.2761, Val Accuracy: 0.6295
Epoch 4319/10000, Train Loss: 1.2006, Train Accuracy: 0.7143, Val Loss: 1.2760, Val Accuracy: 0.6295
Epoch 4320/10000, Train Loss: 1.1926, Train Accuracy: 0.7321, Val Loss: 1.2758, Val Accuracy: 0.6295
Epoch 4321/10000, Train Loss: 1.1961, Train Accuracy: 0.7243, Val Loss: 1.2757, Val Accuracy: 0.6295
Epoch 4322/10000, Train Loss: 1.1964, Train Accuracy: 0.7243, Val Loss: 1.2756, Val Accuracy: 0.6295
Epoch 4323/10000, Train Loss: 1.2015, Train Accuracy: 0.7165, Val Loss: 1.2755, Val Accuracy: 0.6295
Epoch 4324/10000, Train Loss: 1.2006, Train Accuracy: 0.7266, Val Loss: 1.2755, Val Accuracy: 0.6295
Epoch 4325/10000, Train Loss: 1.1993, Train Accuracy: 0.7232, Val Loss: 1.2755, Val Accuracy: 0.6295
Epoch 4326/10000, Train Loss: 1.2049, Train Accuracy: 0.7188, Val Loss: 1.2755, Val Accuracy: 0.6295
Epoch 4327/10000, Train Loss: 1.1924, Train Accuracy: 0.7199, Val Loss: 1.2753, Val Accuracy: 0.6295
Epoch 4328/10000, Train Loss: 1.2065, Train Accuracy: 0.6987, Val Loss: 1.2753, Val Accuracy: 0.6295
Epoch 4329/10000, Train Loss: 1.2075, Train Accuracy: 0.7165, Val Loss: 1.2754, Val Accuracy: 0.6295
Epoch 4330/10000, Train Loss: 1.2085, Train Accuracy: 0.7121, Val Loss: 1.2754, Val Accuracy: 0.6295
Epoch 4331/10000, Train Loss: 1.1992, Train Accuracy: 0.7154, Val Loss: 1.2752, Val Accuracy: 0.6295
Epoch 4332/10000, Train Loss: 1.1968, Train Accuracy: 0.7109, Val Loss: 1.2753, Val Accuracy: 0.6295
Epoch 4333/10000, Train Loss: 1.1982, Train Accuracy: 0.7288, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4334/10000, Train Loss: 1.1906, Train Accuracy: 0.7411, Val Loss: 1.2752, Val Accuracy: 0.6295
Epoch 4335/10000, Train Loss: 1.1962, Train Accuracy: 0.7321, Val Loss: 1.2750, Val Accuracy: 0.6295
Epoch 4336/10000, Train Loss: 1.2068, Train Accuracy: 0.7154, Val Loss: 1.2749, Val Accuracy: 0.6295
Epoch 4337/10000, Train Loss: 1.1963, Train Accuracy: 0.7243, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4338/10000, Train Loss: 1.2041, Train Accuracy: 0.7143, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4339/10000, Train Loss: 1.1875, Train Accuracy: 0.7400, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4340/10000, Train Loss: 1.2051, Train Accuracy: 0.7165, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4341/10000, Train Loss: 1.2004, Train Accuracy: 0.7266, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4342/10000, Train Loss: 1.1936, Train Accuracy: 0.7388, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4343/10000, Train Loss: 1.2022, Train Accuracy: 0.7210, Val Loss: 1.2752, Val Accuracy: 0.6295
Epoch 4344/10000, Train Loss: 1.1944, Train Accuracy: 0.7288, Val Loss: 1.2752, Val Accuracy: 0.6295
Epoch 4345/10000, Train Loss: 1.2054, Train Accuracy: 0.7243, Val Loss: 1.2751, Val Accuracy: 0.6295
Epoch 4346/10000, Train Loss: 1.2089, Train Accuracy: 0.7098, Val Loss: 1.2749, Val Accuracy: 0.6295
Epoch 4347/10000, Train Loss: 1.2027, Train Accuracy: 0.7165, Val Loss: 1.2749, Val Accuracy: 0.6295
Epoch 4348/10000, Train Loss: 1.2133, Train Accuracy: 0.6998, Val Loss: 1.2748, Val Accuracy: 0.6295
Epoch 4349/10000, Train Loss: 1.1894, Train Accuracy: 0.7310, Val Loss: 1.2748, Val Accuracy: 0.6295
Epoch 4350/10000, Train Loss: 1.1985, Train Accuracy: 0.7254, Val Loss: 1.2747, Val Accuracy: 0.6295
Epoch 4351/10000, Train Loss: 1.2047, Train Accuracy: 0.7176, Val Loss: 1.2746, Val Accuracy: 0.6295
Epoch 4352/10000, Train Loss: 1.1961, Train Accuracy: 0.7210, Val Loss: 1.2746, Val Accuracy: 0.6295
Epoch 4353/10000, Train Loss: 1.1930, Train Accuracy: 0.7310, Val Loss: 1.2744, Val Accuracy: 0.6295
Epoch 4354/10000, Train Loss: 1.1970, Train Accuracy: 0.7232, Val Loss: 1.2744, Val Accuracy: 0.6295
Epoch 4355/10000, Train Loss: 1.1983, Train Accuracy: 0.7243, Val Loss: 1.2743, Val Accuracy: 0.6295
Epoch 4356/10000, Train Loss: 1.2013, Train Accuracy: 0.7266, Val Loss: 1.2742, Val Accuracy: 0.6295
Epoch 4357/10000, Train Loss: 1.1968, Train Accuracy: 0.7199, Val Loss: 1.2742, Val Accuracy: 0.6295
Epoch 4358/10000, Train Loss: 1.2081, Train Accuracy: 0.7042, Val Loss: 1.2741, Val Accuracy: 0.6295
Epoch 4359/10000, Train Loss: 1.1934, Train Accuracy: 0.7254, Val Loss: 1.2741, Val Accuracy: 0.6295
Epoch 4360/10000, Train Loss: 1.1983, Train Accuracy: 0.7210, Val Loss: 1.2742, Val Accuracy: 0.6295
Epoch 4361/10000, Train Loss: 1.1995, Train Accuracy: 0.7199, Val Loss: 1.2741, Val Accuracy: 0.6250
Epoch 4362/10000, Train Loss: 1.1946, Train Accuracy: 0.7288, Val Loss: 1.2740, Val Accuracy: 0.6295
Epoch 4363/10000, Train Loss: 1.1981, Train Accuracy: 0.7277, Val Loss: 1.2740, Val Accuracy: 0.6295
Epoch 4364/10000, Train Loss: 1.1955, Train Accuracy: 0.7221, Val Loss: 1.2739, Val Accuracy: 0.6295
Epoch 4365/10000, Train Loss: 1.2009, Train Accuracy: 0.7143, Val Loss: 1.2739, Val Accuracy: 0.6295
Epoch 4366/10000, Train Loss: 1.1953, Train Accuracy: 0.7254, Val Loss: 1.2738, Val Accuracy: 0.6295
Epoch 4367/10000, Train Loss: 1.2031, Train Accuracy: 0.7076, Val Loss: 1.2736, Val Accuracy: 0.6295
Epoch 4368/10000, Train Loss: 1.2036, Train Accuracy: 0.7121, Val Loss: 1.2736, Val Accuracy: 0.6295
Epoch 4369/10000, Train Loss: 1.1976, Train Accuracy: 0.7165, Val Loss: 1.2736, Val Accuracy: 0.6295
Epoch 4370/10000, Train Loss: 1.1827, Train Accuracy: 0.7533, Val Loss: 1.2735, Val Accuracy: 0.6295
Epoch 4371/10000, Train Loss: 1.1896, Train Accuracy: 0.7254, Val Loss: 1.2735, Val Accuracy: 0.6295
Epoch 4372/10000, Train Loss: 1.2021, Train Accuracy: 0.7232, Val Loss: 1.2732, Val Accuracy: 0.6295
Epoch 4373/10000, Train Loss: 1.2051, Train Accuracy: 0.7165, Val Loss: 1.2732, Val Accuracy: 0.6295
Epoch 4374/10000, Train Loss: 1.2077, Train Accuracy: 0.7065, Val Loss: 1.2731, Val Accuracy: 0.6295
Epoch 4375/10000, Train Loss: 1.2009, Train Accuracy: 0.7188, Val Loss: 1.2730, Val Accuracy: 0.6295
Epoch 4376/10000, Train Loss: 1.2001, Train Accuracy: 0.7243, Val Loss: 1.2730, Val Accuracy: 0.6295
Epoch 4377/10000, Train Loss: 1.1987, Train Accuracy: 0.7143, Val Loss: 1.2728, Val Accuracy: 0.6295
Epoch 4378/10000, Train Loss: 1.2066, Train Accuracy: 0.7087, Val Loss: 1.2727, Val Accuracy: 0.6295
Epoch 4379/10000, Train Loss: 1.2056, Train Accuracy: 0.7087, Val Loss: 1.2728, Val Accuracy: 0.6250
Epoch 4380/10000, Train Loss: 1.2032, Train Accuracy: 0.7087, Val Loss: 1.2729, Val Accuracy: 0.6295
Epoch 4381/10000, Train Loss: 1.2014, Train Accuracy: 0.7154, Val Loss: 1.2728, Val Accuracy: 0.6295
Epoch 4382/10000, Train Loss: 1.1881, Train Accuracy: 0.7333, Val Loss: 1.2728, Val Accuracy: 0.6295
Epoch 4383/10000, Train Loss: 1.2015, Train Accuracy: 0.7221, Val Loss: 1.2728, Val Accuracy: 0.6295
Epoch 4384/10000, Train Loss: 1.1911, Train Accuracy: 0.7288, Val Loss: 1.2728, Val Accuracy: 0.6295
Epoch 4385/10000, Train Loss: 1.1974, Train Accuracy: 0.7321, Val Loss: 1.2727, Val Accuracy: 0.6295
Epoch 4386/10000, Train Loss: 1.1976, Train Accuracy: 0.7176, Val Loss: 1.2726, Val Accuracy: 0.6295
Epoch 4387/10000, Train Loss: 1.2035, Train Accuracy: 0.7121, Val Loss: 1.2727, Val Accuracy: 0.6295
Epoch 4388/10000, Train Loss: 1.1985, Train Accuracy: 0.7277, Val Loss: 1.2726, Val Accuracy: 0.6250
Epoch 4389/10000, Train Loss: 1.1924, Train Accuracy: 0.7344, Val Loss: 1.2725, Val Accuracy: 0.6250
Epoch 4390/10000, Train Loss: 1.2084, Train Accuracy: 0.7121, Val Loss: 1.2725, Val Accuracy: 0.6250
Epoch 4391/10000, Train Loss: 1.1994, Train Accuracy: 0.7165, Val Loss: 1.2723, Val Accuracy: 0.6250
Epoch 4392/10000, Train Loss: 1.2043, Train Accuracy: 0.7098, Val Loss: 1.2724, Val Accuracy: 0.6250
Epoch 4393/10000, Train Loss: 1.1930, Train Accuracy: 0.7377, Val Loss: 1.2724, Val Accuracy: 0.6250
Epoch 4394/10000, Train Loss: 1.1927, Train Accuracy: 0.7310, Val Loss: 1.2722, Val Accuracy: 0.6339
Epoch 4395/10000, Train Loss: 1.1941, Train Accuracy: 0.7188, Val Loss: 1.2723, Val Accuracy: 0.6295
Epoch 4396/10000, Train Loss: 1.2016, Train Accuracy: 0.7154, Val Loss: 1.2721, Val Accuracy: 0.6295
Epoch 4397/10000, Train Loss: 1.1972, Train Accuracy: 0.7154, Val Loss: 1.2721, Val Accuracy: 0.6295
Epoch 4398/10000, Train Loss: 1.1974, Train Accuracy: 0.7232, Val Loss: 1.2721, Val Accuracy: 0.6295
Epoch 4399/10000, Train Loss: 1.1970, Train Accuracy: 0.7176, Val Loss: 1.2720, Val Accuracy: 0.6295
Epoch 4400/10000, Train Loss: 1.1959, Train Accuracy: 0.7266, Val Loss: 1.2720, Val Accuracy: 0.6295
Epoch 4401/10000, Train Loss: 1.2041, Train Accuracy: 0.7266, Val Loss: 1.2717, Val Accuracy: 0.6295
Epoch 4402/10000, Train Loss: 1.2079, Train Accuracy: 0.7065, Val Loss: 1.2715, Val Accuracy: 0.6295
Epoch 4403/10000, Train Loss: 1.1883, Train Accuracy: 0.7310, Val Loss: 1.2714, Val Accuracy: 0.6295
Epoch 4404/10000, Train Loss: 1.1972, Train Accuracy: 0.7154, Val Loss: 1.2713, Val Accuracy: 0.6295
Epoch 4405/10000, Train Loss: 1.1957, Train Accuracy: 0.7121, Val Loss: 1.2712, Val Accuracy: 0.6295
Epoch 4406/10000, Train Loss: 1.1914, Train Accuracy: 0.7333, Val Loss: 1.2711, Val Accuracy: 0.6295
Epoch 4407/10000, Train Loss: 1.1847, Train Accuracy: 0.7444, Val Loss: 1.2711, Val Accuracy: 0.6295
Epoch 4408/10000, Train Loss: 1.1991, Train Accuracy: 0.7210, Val Loss: 1.2709, Val Accuracy: 0.6295
Epoch 4409/10000, Train Loss: 1.1888, Train Accuracy: 0.7221, Val Loss: 1.2709, Val Accuracy: 0.6339
Epoch 4410/10000, Train Loss: 1.1888, Train Accuracy: 0.7321, Val Loss: 1.2709, Val Accuracy: 0.6295
Epoch 4411/10000, Train Loss: 1.1902, Train Accuracy: 0.7310, Val Loss: 1.2710, Val Accuracy: 0.6295
Epoch 4412/10000, Train Loss: 1.1924, Train Accuracy: 0.7266, Val Loss: 1.2711, Val Accuracy: 0.6295
Epoch 4413/10000, Train Loss: 1.1899, Train Accuracy: 0.7243, Val Loss: 1.2710, Val Accuracy: 0.6295
Epoch 4414/10000, Train Loss: 1.1915, Train Accuracy: 0.7400, Val Loss: 1.2709, Val Accuracy: 0.6295
Epoch 4415/10000, Train Loss: 1.2008, Train Accuracy: 0.7188, Val Loss: 1.2709, Val Accuracy: 0.6295
Epoch 4416/10000, Train Loss: 1.2025, Train Accuracy: 0.7199, Val Loss: 1.2709, Val Accuracy: 0.6295
Epoch 4417/10000, Train Loss: 1.1946, Train Accuracy: 0.7277, Val Loss: 1.2708, Val Accuracy: 0.6295
Epoch 4418/10000, Train Loss: 1.1957, Train Accuracy: 0.7266, Val Loss: 1.2708, Val Accuracy: 0.6295
Epoch 4419/10000, Train Loss: 1.1932, Train Accuracy: 0.7199, Val Loss: 1.2706, Val Accuracy: 0.6295
Epoch 4420/10000, Train Loss: 1.1974, Train Accuracy: 0.7176, Val Loss: 1.2706, Val Accuracy: 0.6295
Epoch 4421/10000, Train Loss: 1.1997, Train Accuracy: 0.7154, Val Loss: 1.2706, Val Accuracy: 0.6295
Epoch 4422/10000, Train Loss: 1.1835, Train Accuracy: 0.7344, Val Loss: 1.2706, Val Accuracy: 0.6295
Epoch 4423/10000, Train Loss: 1.1962, Train Accuracy: 0.7121, Val Loss: 1.2705, Val Accuracy: 0.6295
Epoch 4424/10000, Train Loss: 1.1977, Train Accuracy: 0.7321, Val Loss: 1.2703, Val Accuracy: 0.6295
Epoch 4425/10000, Train Loss: 1.1944, Train Accuracy: 0.7221, Val Loss: 1.2703, Val Accuracy: 0.6295
Epoch 4426/10000, Train Loss: 1.1918, Train Accuracy: 0.7277, Val Loss: 1.2702, Val Accuracy: 0.6295
Epoch 4427/10000, Train Loss: 1.1925, Train Accuracy: 0.7221, Val Loss: 1.2700, Val Accuracy: 0.6295
Epoch 4428/10000, Train Loss: 1.1918, Train Accuracy: 0.7232, Val Loss: 1.2700, Val Accuracy: 0.6339
Epoch 4429/10000, Train Loss: 1.1869, Train Accuracy: 0.7266, Val Loss: 1.2699, Val Accuracy: 0.6295
Epoch 4430/10000, Train Loss: 1.1893, Train Accuracy: 0.7366, Val Loss: 1.2698, Val Accuracy: 0.6295
Epoch 4431/10000, Train Loss: 1.1937, Train Accuracy: 0.7176, Val Loss: 1.2698, Val Accuracy: 0.6339
Epoch 4432/10000, Train Loss: 1.2102, Train Accuracy: 0.6998, Val Loss: 1.2697, Val Accuracy: 0.6339
Epoch 4433/10000, Train Loss: 1.1857, Train Accuracy: 0.7388, Val Loss: 1.2697, Val Accuracy: 0.6339
Epoch 4434/10000, Train Loss: 1.1998, Train Accuracy: 0.7109, Val Loss: 1.2695, Val Accuracy: 0.6339
Epoch 4435/10000, Train Loss: 1.1944, Train Accuracy: 0.7266, Val Loss: 1.2695, Val Accuracy: 0.6295
Epoch 4436/10000, Train Loss: 1.1850, Train Accuracy: 0.7455, Val Loss: 1.2695, Val Accuracy: 0.6295
Epoch 4437/10000, Train Loss: 1.2002, Train Accuracy: 0.7109, Val Loss: 1.2694, Val Accuracy: 0.6295
Epoch 4438/10000, Train Loss: 1.2134, Train Accuracy: 0.7020, Val Loss: 1.2694, Val Accuracy: 0.6295
Epoch 4439/10000, Train Loss: 1.1938, Train Accuracy: 0.7299, Val Loss: 1.2692, Val Accuracy: 0.6339
Epoch 4440/10000, Train Loss: 1.1987, Train Accuracy: 0.7221, Val Loss: 1.2692, Val Accuracy: 0.6339
Epoch 4441/10000, Train Loss: 1.1907, Train Accuracy: 0.7288, Val Loss: 1.2692, Val Accuracy: 0.6339
Epoch 4442/10000, Train Loss: 1.1971, Train Accuracy: 0.7210, Val Loss: 1.2693, Val Accuracy: 0.6295
Epoch 4443/10000, Train Loss: 1.1779, Train Accuracy: 0.7400, Val Loss: 1.2694, Val Accuracy: 0.6295
Epoch 4444/10000, Train Loss: 1.2098, Train Accuracy: 0.7109, Val Loss: 1.2694, Val Accuracy: 0.6295
Epoch 4445/10000, Train Loss: 1.1987, Train Accuracy: 0.7254, Val Loss: 1.2693, Val Accuracy: 0.6295
Epoch 4446/10000, Train Loss: 1.2037, Train Accuracy: 0.7176, Val Loss: 1.2693, Val Accuracy: 0.6295
Epoch 4447/10000, Train Loss: 1.1964, Train Accuracy: 0.7299, Val Loss: 1.2691, Val Accuracy: 0.6339
Epoch 4448/10000, Train Loss: 1.1869, Train Accuracy: 0.7344, Val Loss: 1.2690, Val Accuracy: 0.6339
Epoch 4449/10000, Train Loss: 1.1839, Train Accuracy: 0.7366, Val Loss: 1.2690, Val Accuracy: 0.6339
Epoch 4450/10000, Train Loss: 1.1997, Train Accuracy: 0.7221, Val Loss: 1.2688, Val Accuracy: 0.6339
Epoch 4451/10000, Train Loss: 1.2036, Train Accuracy: 0.7109, Val Loss: 1.2687, Val Accuracy: 0.6339
Epoch 4452/10000, Train Loss: 1.1977, Train Accuracy: 0.7210, Val Loss: 1.2687, Val Accuracy: 0.6339
Epoch 4453/10000, Train Loss: 1.2004, Train Accuracy: 0.7176, Val Loss: 1.2686, Val Accuracy: 0.6384
Epoch 4454/10000, Train Loss: 1.1884, Train Accuracy: 0.7333, Val Loss: 1.2686, Val Accuracy: 0.6384
Epoch 4455/10000, Train Loss: 1.1911, Train Accuracy: 0.7254, Val Loss: 1.2685, Val Accuracy: 0.6429
Epoch 4456/10000, Train Loss: 1.1780, Train Accuracy: 0.7444, Val Loss: 1.2685, Val Accuracy: 0.6339
Epoch 4457/10000, Train Loss: 1.2067, Train Accuracy: 0.7020, Val Loss: 1.2686, Val Accuracy: 0.6339
Epoch 4458/10000, Train Loss: 1.2081, Train Accuracy: 0.7076, Val Loss: 1.2686, Val Accuracy: 0.6339
Epoch 4459/10000, Train Loss: 1.1944, Train Accuracy: 0.7310, Val Loss: 1.2685, Val Accuracy: 0.6384
Epoch 4460/10000, Train Loss: 1.1896, Train Accuracy: 0.7199, Val Loss: 1.2686, Val Accuracy: 0.6295
Epoch 4461/10000, Train Loss: 1.1913, Train Accuracy: 0.7243, Val Loss: 1.2687, Val Accuracy: 0.6384
Epoch 4462/10000, Train Loss: 1.1978, Train Accuracy: 0.7277, Val Loss: 1.2686, Val Accuracy: 0.6339
Epoch 4463/10000, Train Loss: 1.1883, Train Accuracy: 0.7310, Val Loss: 1.2686, Val Accuracy: 0.6339
Epoch 4464/10000, Train Loss: 1.1942, Train Accuracy: 0.7221, Val Loss: 1.2686, Val Accuracy: 0.6339
Epoch 4465/10000, Train Loss: 1.1883, Train Accuracy: 0.7310, Val Loss: 1.2685, Val Accuracy: 0.6339
Epoch 4466/10000, Train Loss: 1.1923, Train Accuracy: 0.7344, Val Loss: 1.2684, Val Accuracy: 0.6339
Epoch 4467/10000, Train Loss: 1.1878, Train Accuracy: 0.7321, Val Loss: 1.2684, Val Accuracy: 0.6339
Epoch 4468/10000, Train Loss: 1.1724, Train Accuracy: 0.7567, Val Loss: 1.2684, Val Accuracy: 0.6339
Epoch 4469/10000, Train Loss: 1.1921, Train Accuracy: 0.7310, Val Loss: 1.2682, Val Accuracy: 0.6339
Epoch 4470/10000, Train Loss: 1.2003, Train Accuracy: 0.7143, Val Loss: 1.2682, Val Accuracy: 0.6339
Epoch 4471/10000, Train Loss: 1.1989, Train Accuracy: 0.7221, Val Loss: 1.2683, Val Accuracy: 0.6339
Epoch 4472/10000, Train Loss: 1.1989, Train Accuracy: 0.7176, Val Loss: 1.2683, Val Accuracy: 0.6339
Epoch 4473/10000, Train Loss: 1.1919, Train Accuracy: 0.7310, Val Loss: 1.2683, Val Accuracy: 0.6339
Epoch 4474/10000, Train Loss: 1.1883, Train Accuracy: 0.7366, Val Loss: 1.2682, Val Accuracy: 0.6339
Epoch 4475/10000, Train Loss: 1.1799, Train Accuracy: 0.7467, Val Loss: 1.2681, Val Accuracy: 0.6339
Epoch 4476/10000, Train Loss: 1.1989, Train Accuracy: 0.7121, Val Loss: 1.2680, Val Accuracy: 0.6339
Epoch 4477/10000, Train Loss: 1.1987, Train Accuracy: 0.7121, Val Loss: 1.2681, Val Accuracy: 0.6339
Epoch 4478/10000, Train Loss: 1.1935, Train Accuracy: 0.7221, Val Loss: 1.2679, Val Accuracy: 0.6339
Epoch 4479/10000, Train Loss: 1.1932, Train Accuracy: 0.7210, Val Loss: 1.2679, Val Accuracy: 0.6339
Epoch 4480/10000, Train Loss: 1.1969, Train Accuracy: 0.7243, Val Loss: 1.2677, Val Accuracy: 0.6339
Epoch 4481/10000, Train Loss: 1.1977, Train Accuracy: 0.7176, Val Loss: 1.2678, Val Accuracy: 0.6339
Epoch 4482/10000, Train Loss: 1.1832, Train Accuracy: 0.7411, Val Loss: 1.2679, Val Accuracy: 0.6339
Epoch 4483/10000, Train Loss: 1.1902, Train Accuracy: 0.7366, Val Loss: 1.2678, Val Accuracy: 0.6295
Epoch 4484/10000, Train Loss: 1.1846, Train Accuracy: 0.7333, Val Loss: 1.2678, Val Accuracy: 0.6295
Epoch 4485/10000, Train Loss: 1.1886, Train Accuracy: 0.7277, Val Loss: 1.2677, Val Accuracy: 0.6295
Epoch 4486/10000, Train Loss: 1.1909, Train Accuracy: 0.7277, Val Loss: 1.2678, Val Accuracy: 0.6295
Epoch 4487/10000, Train Loss: 1.1904, Train Accuracy: 0.7243, Val Loss: 1.2677, Val Accuracy: 0.6295
Epoch 4488/10000, Train Loss: 1.1778, Train Accuracy: 0.7489, Val Loss: 1.2677, Val Accuracy: 0.6339
Epoch 4489/10000, Train Loss: 1.1967, Train Accuracy: 0.7199, Val Loss: 1.2677, Val Accuracy: 0.6339
Epoch 4490/10000, Train Loss: 1.1865, Train Accuracy: 0.7310, Val Loss: 1.2676, Val Accuracy: 0.6384
Epoch 4491/10000, Train Loss: 1.1900, Train Accuracy: 0.7333, Val Loss: 1.2675, Val Accuracy: 0.6384
Epoch 4492/10000, Train Loss: 1.1939, Train Accuracy: 0.7333, Val Loss: 1.2676, Val Accuracy: 0.6384
Epoch 4493/10000, Train Loss: 1.1900, Train Accuracy: 0.7254, Val Loss: 1.2675, Val Accuracy: 0.6384
Epoch 4494/10000, Train Loss: 1.1992, Train Accuracy: 0.7154, Val Loss: 1.2674, Val Accuracy: 0.6384
Epoch 4495/10000, Train Loss: 1.2021, Train Accuracy: 0.7243, Val Loss: 1.2674, Val Accuracy: 0.6384
Epoch 4496/10000, Train Loss: 1.1870, Train Accuracy: 0.7310, Val Loss: 1.2674, Val Accuracy: 0.6384
Epoch 4497/10000, Train Loss: 1.2006, Train Accuracy: 0.7221, Val Loss: 1.2674, Val Accuracy: 0.6384
Epoch 4498/10000, Train Loss: 1.1907, Train Accuracy: 0.7299, Val Loss: 1.2673, Val Accuracy: 0.6384
Epoch 4499/10000, Train Loss: 1.1911, Train Accuracy: 0.7243, Val Loss: 1.2672, Val Accuracy: 0.6384
Epoch 4500/10000, Train Loss: 1.1900, Train Accuracy: 0.7199, Val Loss: 1.2673, Val Accuracy: 0.6429
Epoch 4501/10000, Train Loss: 1.1913, Train Accuracy: 0.7344, Val Loss: 1.2672, Val Accuracy: 0.6384
Epoch 4502/10000, Train Loss: 1.1942, Train Accuracy: 0.7199, Val Loss: 1.2672, Val Accuracy: 0.6339
Epoch 4503/10000, Train Loss: 1.1739, Train Accuracy: 0.7455, Val Loss: 1.2672, Val Accuracy: 0.6384
Epoch 4504/10000, Train Loss: 1.1951, Train Accuracy: 0.7199, Val Loss: 1.2670, Val Accuracy: 0.6339
Epoch 4505/10000, Train Loss: 1.2040, Train Accuracy: 0.7042, Val Loss: 1.2669, Val Accuracy: 0.6384
Epoch 4506/10000, Train Loss: 1.1845, Train Accuracy: 0.7411, Val Loss: 1.2668, Val Accuracy: 0.6384
Epoch 4507/10000, Train Loss: 1.1912, Train Accuracy: 0.7266, Val Loss: 1.2668, Val Accuracy: 0.6384
Epoch 4508/10000, Train Loss: 1.1833, Train Accuracy: 0.7400, Val Loss: 1.2668, Val Accuracy: 0.6384
Epoch 4509/10000, Train Loss: 1.1883, Train Accuracy: 0.7277, Val Loss: 1.2666, Val Accuracy: 0.6384
Epoch 4510/10000, Train Loss: 1.1916, Train Accuracy: 0.7321, Val Loss: 1.2666, Val Accuracy: 0.6384
Epoch 4511/10000, Train Loss: 1.1950, Train Accuracy: 0.7221, Val Loss: 1.2667, Val Accuracy: 0.6384
Epoch 4512/10000, Train Loss: 1.1995, Train Accuracy: 0.7221, Val Loss: 1.2666, Val Accuracy: 0.6339
Epoch 4513/10000, Train Loss: 1.1982, Train Accuracy: 0.7109, Val Loss: 1.2665, Val Accuracy: 0.6339
Epoch 4514/10000, Train Loss: 1.1865, Train Accuracy: 0.7344, Val Loss: 1.2664, Val Accuracy: 0.6295
Epoch 4515/10000, Train Loss: 1.1943, Train Accuracy: 0.7243, Val Loss: 1.2663, Val Accuracy: 0.6384
Epoch 4516/10000, Train Loss: 1.1976, Train Accuracy: 0.7109, Val Loss: 1.2663, Val Accuracy: 0.6384
Epoch 4517/10000, Train Loss: 1.1905, Train Accuracy: 0.7210, Val Loss: 1.2662, Val Accuracy: 0.6384
Epoch 4518/10000, Train Loss: 1.1862, Train Accuracy: 0.7355, Val Loss: 1.2662, Val Accuracy: 0.6384
Epoch 4519/10000, Train Loss: 1.1870, Train Accuracy: 0.7299, Val Loss: 1.2661, Val Accuracy: 0.6384
Epoch 4520/10000, Train Loss: 1.1938, Train Accuracy: 0.7243, Val Loss: 1.2660, Val Accuracy: 0.6384
Epoch 4521/10000, Train Loss: 1.1908, Train Accuracy: 0.7266, Val Loss: 1.2660, Val Accuracy: 0.6339
Epoch 4522/10000, Train Loss: 1.1885, Train Accuracy: 0.7299, Val Loss: 1.2659, Val Accuracy: 0.6384
Epoch 4523/10000, Train Loss: 1.1878, Train Accuracy: 0.7266, Val Loss: 1.2658, Val Accuracy: 0.6384
Epoch 4524/10000, Train Loss: 1.1833, Train Accuracy: 0.7400, Val Loss: 1.2658, Val Accuracy: 0.6339
Epoch 4525/10000, Train Loss: 1.1799, Train Accuracy: 0.7467, Val Loss: 1.2659, Val Accuracy: 0.6339
Epoch 4526/10000, Train Loss: 1.1976, Train Accuracy: 0.7199, Val Loss: 1.2657, Val Accuracy: 0.6384
Epoch 4527/10000, Train Loss: 1.1862, Train Accuracy: 0.7333, Val Loss: 1.2655, Val Accuracy: 0.6384
Epoch 4528/10000, Train Loss: 1.1835, Train Accuracy: 0.7355, Val Loss: 1.2655, Val Accuracy: 0.6384
Epoch 4529/10000, Train Loss: 1.1862, Train Accuracy: 0.7299, Val Loss: 1.2654, Val Accuracy: 0.6339
Epoch 4530/10000, Train Loss: 1.1935, Train Accuracy: 0.7266, Val Loss: 1.2654, Val Accuracy: 0.6339
Epoch 4531/10000, Train Loss: 1.1846, Train Accuracy: 0.7355, Val Loss: 1.2653, Val Accuracy: 0.6339
Epoch 4532/10000, Train Loss: 1.1842, Train Accuracy: 0.7411, Val Loss: 1.2652, Val Accuracy: 0.6339
Epoch 4533/10000, Train Loss: 1.1759, Train Accuracy: 0.7478, Val Loss: 1.2652, Val Accuracy: 0.6339
Epoch 4534/10000, Train Loss: 1.1775, Train Accuracy: 0.7411, Val Loss: 1.2651, Val Accuracy: 0.6384
Epoch 4535/10000, Train Loss: 1.1781, Train Accuracy: 0.7344, Val Loss: 1.2649, Val Accuracy: 0.6339
Epoch 4536/10000, Train Loss: 1.1838, Train Accuracy: 0.7321, Val Loss: 1.2648, Val Accuracy: 0.6384
Epoch 4537/10000, Train Loss: 1.1919, Train Accuracy: 0.7254, Val Loss: 1.2649, Val Accuracy: 0.6384
Epoch 4538/10000, Train Loss: 1.1980, Train Accuracy: 0.7243, Val Loss: 1.2648, Val Accuracy: 0.6384
Epoch 4539/10000, Train Loss: 1.1898, Train Accuracy: 0.7210, Val Loss: 1.2648, Val Accuracy: 0.6384
Epoch 4540/10000, Train Loss: 1.1910, Train Accuracy: 0.7333, Val Loss: 1.2648, Val Accuracy: 0.6429
Epoch 4541/10000, Train Loss: 1.1844, Train Accuracy: 0.7422, Val Loss: 1.2647, Val Accuracy: 0.6429
Epoch 4542/10000, Train Loss: 1.1890, Train Accuracy: 0.7321, Val Loss: 1.2648, Val Accuracy: 0.6429
Epoch 4543/10000, Train Loss: 1.1906, Train Accuracy: 0.7288, Val Loss: 1.2647, Val Accuracy: 0.6429
Epoch 4544/10000, Train Loss: 1.1868, Train Accuracy: 0.7388, Val Loss: 1.2647, Val Accuracy: 0.6429
Epoch 4545/10000, Train Loss: 1.1892, Train Accuracy: 0.7467, Val Loss: 1.2646, Val Accuracy: 0.6384
Epoch 4546/10000, Train Loss: 1.1783, Train Accuracy: 0.7533, Val Loss: 1.2645, Val Accuracy: 0.6384
Epoch 4547/10000, Train Loss: 1.1968, Train Accuracy: 0.7232, Val Loss: 1.2643, Val Accuracy: 0.6384
Epoch 4548/10000, Train Loss: 1.1871, Train Accuracy: 0.7277, Val Loss: 1.2645, Val Accuracy: 0.6384
Epoch 4549/10000, Train Loss: 1.1924, Train Accuracy: 0.7232, Val Loss: 1.2646, Val Accuracy: 0.6339
Epoch 4550/10000, Train Loss: 1.1858, Train Accuracy: 0.7199, Val Loss: 1.2646, Val Accuracy: 0.6384
Epoch 4551/10000, Train Loss: 1.1984, Train Accuracy: 0.7154, Val Loss: 1.2645, Val Accuracy: 0.6384
Epoch 4552/10000, Train Loss: 1.1839, Train Accuracy: 0.7355, Val Loss: 1.2644, Val Accuracy: 0.6384
Epoch 4553/10000, Train Loss: 1.1796, Train Accuracy: 0.7489, Val Loss: 1.2644, Val Accuracy: 0.6429
Epoch 4554/10000, Train Loss: 1.1896, Train Accuracy: 0.7299, Val Loss: 1.2643, Val Accuracy: 0.6384
Epoch 4555/10000, Train Loss: 1.1731, Train Accuracy: 0.7500, Val Loss: 1.2641, Val Accuracy: 0.6384
Epoch 4556/10000, Train Loss: 1.1778, Train Accuracy: 0.7500, Val Loss: 1.2640, Val Accuracy: 0.6429
Epoch 4557/10000, Train Loss: 1.1926, Train Accuracy: 0.7266, Val Loss: 1.2640, Val Accuracy: 0.6384
Epoch 4558/10000, Train Loss: 1.1989, Train Accuracy: 0.7199, Val Loss: 1.2640, Val Accuracy: 0.6339
Epoch 4559/10000, Train Loss: 1.1822, Train Accuracy: 0.7277, Val Loss: 1.2638, Val Accuracy: 0.6384
Epoch 4560/10000, Train Loss: 1.1871, Train Accuracy: 0.7388, Val Loss: 1.2639, Val Accuracy: 0.6384
Epoch 4561/10000, Train Loss: 1.1973, Train Accuracy: 0.7188, Val Loss: 1.2641, Val Accuracy: 0.6384
Epoch 4562/10000, Train Loss: 1.1839, Train Accuracy: 0.7388, Val Loss: 1.2639, Val Accuracy: 0.6384
Epoch 4563/10000, Train Loss: 1.1748, Train Accuracy: 0.7533, Val Loss: 1.2638, Val Accuracy: 0.6429
Epoch 4564/10000, Train Loss: 1.1910, Train Accuracy: 0.7266, Val Loss: 1.2638, Val Accuracy: 0.6429
Epoch 4565/10000, Train Loss: 1.1819, Train Accuracy: 0.7299, Val Loss: 1.2637, Val Accuracy: 0.6384
Epoch 4566/10000, Train Loss: 1.1841, Train Accuracy: 0.7355, Val Loss: 1.2635, Val Accuracy: 0.6384
Epoch 4567/10000, Train Loss: 1.1949, Train Accuracy: 0.7154, Val Loss: 1.2635, Val Accuracy: 0.6429
Epoch 4568/10000, Train Loss: 1.1851, Train Accuracy: 0.7243, Val Loss: 1.2634, Val Accuracy: 0.6429
Epoch 4569/10000, Train Loss: 1.1809, Train Accuracy: 0.7377, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4570/10000, Train Loss: 1.1803, Train Accuracy: 0.7344, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4571/10000, Train Loss: 1.1891, Train Accuracy: 0.7254, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4572/10000, Train Loss: 1.1813, Train Accuracy: 0.7310, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4573/10000, Train Loss: 1.1825, Train Accuracy: 0.7444, Val Loss: 1.2634, Val Accuracy: 0.6473
Epoch 4574/10000, Train Loss: 1.1865, Train Accuracy: 0.7254, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4575/10000, Train Loss: 1.1874, Train Accuracy: 0.7266, Val Loss: 1.2633, Val Accuracy: 0.6429
Epoch 4576/10000, Train Loss: 1.1904, Train Accuracy: 0.7355, Val Loss: 1.2631, Val Accuracy: 0.6429
Epoch 4577/10000, Train Loss: 1.1854, Train Accuracy: 0.7400, Val Loss: 1.2629, Val Accuracy: 0.6429
Epoch 4578/10000, Train Loss: 1.1841, Train Accuracy: 0.7388, Val Loss: 1.2629, Val Accuracy: 0.6429
Epoch 4579/10000, Train Loss: 1.1939, Train Accuracy: 0.7221, Val Loss: 1.2629, Val Accuracy: 0.6429
Epoch 4580/10000, Train Loss: 1.1901, Train Accuracy: 0.7344, Val Loss: 1.2628, Val Accuracy: 0.6429
Epoch 4581/10000, Train Loss: 1.1843, Train Accuracy: 0.7344, Val Loss: 1.2626, Val Accuracy: 0.6429
Epoch 4582/10000, Train Loss: 1.1895, Train Accuracy: 0.7266, Val Loss: 1.2627, Val Accuracy: 0.6429
Epoch 4583/10000, Train Loss: 1.1916, Train Accuracy: 0.7310, Val Loss: 1.2627, Val Accuracy: 0.6429
Epoch 4584/10000, Train Loss: 1.1919, Train Accuracy: 0.7176, Val Loss: 1.2628, Val Accuracy: 0.6429
Epoch 4585/10000, Train Loss: 1.1748, Train Accuracy: 0.7489, Val Loss: 1.2627, Val Accuracy: 0.6429
Epoch 4586/10000, Train Loss: 1.1960, Train Accuracy: 0.7254, Val Loss: 1.2626, Val Accuracy: 0.6429
Epoch 4587/10000, Train Loss: 1.1899, Train Accuracy: 0.7277, Val Loss: 1.2627, Val Accuracy: 0.6473
Epoch 4588/10000, Train Loss: 1.1867, Train Accuracy: 0.7321, Val Loss: 1.2627, Val Accuracy: 0.6473
Epoch 4589/10000, Train Loss: 1.1818, Train Accuracy: 0.7400, Val Loss: 1.2627, Val Accuracy: 0.6473
Epoch 4590/10000, Train Loss: 1.1782, Train Accuracy: 0.7388, Val Loss: 1.2627, Val Accuracy: 0.6429
Epoch 4591/10000, Train Loss: 1.1868, Train Accuracy: 0.7321, Val Loss: 1.2626, Val Accuracy: 0.6429
Epoch 4592/10000, Train Loss: 1.1806, Train Accuracy: 0.7377, Val Loss: 1.2626, Val Accuracy: 0.6429
Epoch 4593/10000, Train Loss: 1.1788, Train Accuracy: 0.7366, Val Loss: 1.2626, Val Accuracy: 0.6429
Epoch 4594/10000, Train Loss: 1.1862, Train Accuracy: 0.7433, Val Loss: 1.2625, Val Accuracy: 0.6473
Epoch 4595/10000, Train Loss: 1.1815, Train Accuracy: 0.7344, Val Loss: 1.2625, Val Accuracy: 0.6429
Epoch 4596/10000, Train Loss: 1.1831, Train Accuracy: 0.7377, Val Loss: 1.2625, Val Accuracy: 0.6429
Epoch 4597/10000, Train Loss: 1.1971, Train Accuracy: 0.7210, Val Loss: 1.2624, Val Accuracy: 0.6429
Epoch 4598/10000, Train Loss: 1.1814, Train Accuracy: 0.7288, Val Loss: 1.2622, Val Accuracy: 0.6429
Epoch 4599/10000, Train Loss: 1.1763, Train Accuracy: 0.7422, Val Loss: 1.2621, Val Accuracy: 0.6429
Epoch 4600/10000, Train Loss: 1.1860, Train Accuracy: 0.7299, Val Loss: 1.2623, Val Accuracy: 0.6473
Epoch 4601/10000, Train Loss: 1.1722, Train Accuracy: 0.7422, Val Loss: 1.2622, Val Accuracy: 0.6473
Epoch 4602/10000, Train Loss: 1.1883, Train Accuracy: 0.7266, Val Loss: 1.2620, Val Accuracy: 0.6473
Epoch 4603/10000, Train Loss: 1.1749, Train Accuracy: 0.7467, Val Loss: 1.2619, Val Accuracy: 0.6473
Epoch 4604/10000, Train Loss: 1.1881, Train Accuracy: 0.7321, Val Loss: 1.2618, Val Accuracy: 0.6429
Epoch 4605/10000, Train Loss: 1.1963, Train Accuracy: 0.7210, Val Loss: 1.2618, Val Accuracy: 0.6429
Epoch 4606/10000, Train Loss: 1.1766, Train Accuracy: 0.7388, Val Loss: 1.2618, Val Accuracy: 0.6429
Epoch 4607/10000, Train Loss: 1.1670, Train Accuracy: 0.7600, Val Loss: 1.2618, Val Accuracy: 0.6429
Epoch 4608/10000, Train Loss: 1.1900, Train Accuracy: 0.7288, Val Loss: 1.2617, Val Accuracy: 0.6384
Epoch 4609/10000, Train Loss: 1.1878, Train Accuracy: 0.7288, Val Loss: 1.2616, Val Accuracy: 0.6429
Epoch 4610/10000, Train Loss: 1.1812, Train Accuracy: 0.7299, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4611/10000, Train Loss: 1.1829, Train Accuracy: 0.7344, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4612/10000, Train Loss: 1.2007, Train Accuracy: 0.7065, Val Loss: 1.2615, Val Accuracy: 0.6429
Epoch 4613/10000, Train Loss: 1.1884, Train Accuracy: 0.7333, Val Loss: 1.2614, Val Accuracy: 0.6473
Epoch 4614/10000, Train Loss: 1.1947, Train Accuracy: 0.7266, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4615/10000, Train Loss: 1.1843, Train Accuracy: 0.7333, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4616/10000, Train Loss: 1.1852, Train Accuracy: 0.7344, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4617/10000, Train Loss: 1.1919, Train Accuracy: 0.7221, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4618/10000, Train Loss: 1.1998, Train Accuracy: 0.7176, Val Loss: 1.2614, Val Accuracy: 0.6429
Epoch 4619/10000, Train Loss: 1.1761, Train Accuracy: 0.7422, Val Loss: 1.2612, Val Accuracy: 0.6429
Epoch 4620/10000, Train Loss: 1.1658, Train Accuracy: 0.7489, Val Loss: 1.2612, Val Accuracy: 0.6429
Epoch 4621/10000, Train Loss: 1.1804, Train Accuracy: 0.7478, Val Loss: 1.2610, Val Accuracy: 0.6429
Epoch 4622/10000, Train Loss: 1.1799, Train Accuracy: 0.7344, Val Loss: 1.2610, Val Accuracy: 0.6429
Epoch 4623/10000, Train Loss: 1.1807, Train Accuracy: 0.7433, Val Loss: 1.2610, Val Accuracy: 0.6429
Epoch 4624/10000, Train Loss: 1.1837, Train Accuracy: 0.7277, Val Loss: 1.2610, Val Accuracy: 0.6429
Epoch 4625/10000, Train Loss: 1.1789, Train Accuracy: 0.7321, Val Loss: 1.2608, Val Accuracy: 0.6384
Epoch 4626/10000, Train Loss: 1.1720, Train Accuracy: 0.7433, Val Loss: 1.2607, Val Accuracy: 0.6429
Epoch 4627/10000, Train Loss: 1.1873, Train Accuracy: 0.7232, Val Loss: 1.2607, Val Accuracy: 0.6429
Epoch 4628/10000, Train Loss: 1.1811, Train Accuracy: 0.7333, Val Loss: 1.2607, Val Accuracy: 0.6473
Epoch 4629/10000, Train Loss: 1.1818, Train Accuracy: 0.7310, Val Loss: 1.2607, Val Accuracy: 0.6473
Epoch 4630/10000, Train Loss: 1.1882, Train Accuracy: 0.7254, Val Loss: 1.2606, Val Accuracy: 0.6429
Epoch 4631/10000, Train Loss: 1.1831, Train Accuracy: 0.7366, Val Loss: 1.2606, Val Accuracy: 0.6473
Epoch 4632/10000, Train Loss: 1.1847, Train Accuracy: 0.7333, Val Loss: 1.2605, Val Accuracy: 0.6473
Epoch 4633/10000, Train Loss: 1.1644, Train Accuracy: 0.7612, Val Loss: 1.2605, Val Accuracy: 0.6429
Epoch 4634/10000, Train Loss: 1.1967, Train Accuracy: 0.7254, Val Loss: 1.2605, Val Accuracy: 0.6473
Epoch 4635/10000, Train Loss: 1.1730, Train Accuracy: 0.7433, Val Loss: 1.2605, Val Accuracy: 0.6518
Epoch 4636/10000, Train Loss: 1.1790, Train Accuracy: 0.7355, Val Loss: 1.2605, Val Accuracy: 0.6518
Epoch 4637/10000, Train Loss: 1.1952, Train Accuracy: 0.7121, Val Loss: 1.2605, Val Accuracy: 0.6473
Epoch 4638/10000, Train Loss: 1.1787, Train Accuracy: 0.7377, Val Loss: 1.2605, Val Accuracy: 0.6518
Epoch 4639/10000, Train Loss: 1.1774, Train Accuracy: 0.7533, Val Loss: 1.2603, Val Accuracy: 0.6518
Epoch 4640/10000, Train Loss: 1.1821, Train Accuracy: 0.7355, Val Loss: 1.2603, Val Accuracy: 0.6518
Epoch 4641/10000, Train Loss: 1.1744, Train Accuracy: 0.7500, Val Loss: 1.2603, Val Accuracy: 0.6518
Epoch 4642/10000, Train Loss: 1.1785, Train Accuracy: 0.7444, Val Loss: 1.2602, Val Accuracy: 0.6473
Epoch 4643/10000, Train Loss: 1.1907, Train Accuracy: 0.7243, Val Loss: 1.2602, Val Accuracy: 0.6473
Epoch 4644/10000, Train Loss: 1.1906, Train Accuracy: 0.7377, Val Loss: 1.2604, Val Accuracy: 0.6473
Epoch 4645/10000, Train Loss: 1.1836, Train Accuracy: 0.7400, Val Loss: 1.2603, Val Accuracy: 0.6473
Epoch 4646/10000, Train Loss: 1.1629, Train Accuracy: 0.7533, Val Loss: 1.2602, Val Accuracy: 0.6473
Epoch 4647/10000, Train Loss: 1.1888, Train Accuracy: 0.7254, Val Loss: 1.2602, Val Accuracy: 0.6518
Epoch 4648/10000, Train Loss: 1.1809, Train Accuracy: 0.7266, Val Loss: 1.2601, Val Accuracy: 0.6518
Epoch 4649/10000, Train Loss: 1.1832, Train Accuracy: 0.7310, Val Loss: 1.2602, Val Accuracy: 0.6518
Epoch 4650/10000, Train Loss: 1.1908, Train Accuracy: 0.7277, Val Loss: 1.2604, Val Accuracy: 0.6429
Epoch 4651/10000, Train Loss: 1.1908, Train Accuracy: 0.7266, Val Loss: 1.2603, Val Accuracy: 0.6518
Epoch 4652/10000, Train Loss: 1.1930, Train Accuracy: 0.7221, Val Loss: 1.2603, Val Accuracy: 0.6518
Epoch 4653/10000, Train Loss: 1.1822, Train Accuracy: 0.7366, Val Loss: 1.2601, Val Accuracy: 0.6473
Epoch 4654/10000, Train Loss: 1.1823, Train Accuracy: 0.7433, Val Loss: 1.2601, Val Accuracy: 0.6473
Epoch 4655/10000, Train Loss: 1.1882, Train Accuracy: 0.7299, Val Loss: 1.2600, Val Accuracy: 0.6518
Epoch 4656/10000, Train Loss: 1.1794, Train Accuracy: 0.7400, Val Loss: 1.2600, Val Accuracy: 0.6429
Epoch 4657/10000, Train Loss: 1.1861, Train Accuracy: 0.7243, Val Loss: 1.2602, Val Accuracy: 0.6473
Epoch 4658/10000, Train Loss: 1.1811, Train Accuracy: 0.7310, Val Loss: 1.2601, Val Accuracy: 0.6473
Epoch 4659/10000, Train Loss: 1.1800, Train Accuracy: 0.7411, Val Loss: 1.2597, Val Accuracy: 0.6429
Epoch 4660/10000, Train Loss: 1.1828, Train Accuracy: 0.7344, Val Loss: 1.2598, Val Accuracy: 0.6429
Epoch 4661/10000, Train Loss: 1.1880, Train Accuracy: 0.7355, Val Loss: 1.2599, Val Accuracy: 0.6473
Epoch 4662/10000, Train Loss: 1.1886, Train Accuracy: 0.7277, Val Loss: 1.2599, Val Accuracy: 0.6473
Epoch 4663/10000, Train Loss: 1.1867, Train Accuracy: 0.7277, Val Loss: 1.2597, Val Accuracy: 0.6473
Epoch 4664/10000, Train Loss: 1.1733, Train Accuracy: 0.7444, Val Loss: 1.2597, Val Accuracy: 0.6473
Epoch 4665/10000, Train Loss: 1.1763, Train Accuracy: 0.7478, Val Loss: 1.2594, Val Accuracy: 0.6518
Epoch 4666/10000, Train Loss: 1.1947, Train Accuracy: 0.7232, Val Loss: 1.2595, Val Accuracy: 0.6473
Epoch 4667/10000, Train Loss: 1.1833, Train Accuracy: 0.7344, Val Loss: 1.2595, Val Accuracy: 0.6473
Epoch 4668/10000, Train Loss: 1.1893, Train Accuracy: 0.7310, Val Loss: 1.2593, Val Accuracy: 0.6518
Epoch 4669/10000, Train Loss: 1.1764, Train Accuracy: 0.7422, Val Loss: 1.2595, Val Accuracy: 0.6429
Epoch 4670/10000, Train Loss: 1.1727, Train Accuracy: 0.7489, Val Loss: 1.2595, Val Accuracy: 0.6429
Epoch 4671/10000, Train Loss: 1.1928, Train Accuracy: 0.7277, Val Loss: 1.2594, Val Accuracy: 0.6429
Epoch 4672/10000, Train Loss: 1.1889, Train Accuracy: 0.7333, Val Loss: 1.2591, Val Accuracy: 0.6473
Epoch 4673/10000, Train Loss: 1.1841, Train Accuracy: 0.7333, Val Loss: 1.2590, Val Accuracy: 0.6473
Epoch 4674/10000, Train Loss: 1.1782, Train Accuracy: 0.7422, Val Loss: 1.2590, Val Accuracy: 0.6429
Epoch 4675/10000, Train Loss: 1.1791, Train Accuracy: 0.7422, Val Loss: 1.2589, Val Accuracy: 0.6429
Epoch 4676/10000, Train Loss: 1.1858, Train Accuracy: 0.7310, Val Loss: 1.2588, Val Accuracy: 0.6429
Epoch 4677/10000, Train Loss: 1.1928, Train Accuracy: 0.7277, Val Loss: 1.2587, Val Accuracy: 0.6429
Epoch 4678/10000, Train Loss: 1.1835, Train Accuracy: 0.7333, Val Loss: 1.2586, Val Accuracy: 0.6429
Epoch 4679/10000, Train Loss: 1.1590, Train Accuracy: 0.7600, Val Loss: 1.2585, Val Accuracy: 0.6429
Epoch 4680/10000, Train Loss: 1.1913, Train Accuracy: 0.7221, Val Loss: 1.2585, Val Accuracy: 0.6429
Epoch 4681/10000, Train Loss: 1.1897, Train Accuracy: 0.7288, Val Loss: 1.2583, Val Accuracy: 0.6473
Epoch 4682/10000, Train Loss: 1.1911, Train Accuracy: 0.7188, Val Loss: 1.2582, Val Accuracy: 0.6473
Epoch 4683/10000, Train Loss: 1.1783, Train Accuracy: 0.7433, Val Loss: 1.2582, Val Accuracy: 0.6473
Epoch 4684/10000, Train Loss: 1.1761, Train Accuracy: 0.7411, Val Loss: 1.2585, Val Accuracy: 0.6473
Epoch 4685/10000, Train Loss: 1.1727, Train Accuracy: 0.7422, Val Loss: 1.2584, Val Accuracy: 0.6473
Epoch 4686/10000, Train Loss: 1.1765, Train Accuracy: 0.7444, Val Loss: 1.2585, Val Accuracy: 0.6473
Epoch 4687/10000, Train Loss: 1.1892, Train Accuracy: 0.7232, Val Loss: 1.2586, Val Accuracy: 0.6473
Epoch 4688/10000, Train Loss: 1.1792, Train Accuracy: 0.7388, Val Loss: 1.2587, Val Accuracy: 0.6429
Epoch 4689/10000, Train Loss: 1.1817, Train Accuracy: 0.7310, Val Loss: 1.2586, Val Accuracy: 0.6429
Epoch 4690/10000, Train Loss: 1.1848, Train Accuracy: 0.7299, Val Loss: 1.2586, Val Accuracy: 0.6429
Epoch 4691/10000, Train Loss: 1.1843, Train Accuracy: 0.7377, Val Loss: 1.2583, Val Accuracy: 0.6429
Epoch 4692/10000, Train Loss: 1.1713, Train Accuracy: 0.7533, Val Loss: 1.2582, Val Accuracy: 0.6429
Epoch 4693/10000, Train Loss: 1.1794, Train Accuracy: 0.7422, Val Loss: 1.2581, Val Accuracy: 0.6429
Epoch 4694/10000, Train Loss: 1.1753, Train Accuracy: 0.7422, Val Loss: 1.2582, Val Accuracy: 0.6429
Epoch 4695/10000, Train Loss: 1.1819, Train Accuracy: 0.7266, Val Loss: 1.2580, Val Accuracy: 0.6473
Epoch 4696/10000, Train Loss: 1.1710, Train Accuracy: 0.7444, Val Loss: 1.2579, Val Accuracy: 0.6473
Epoch 4697/10000, Train Loss: 1.1714, Train Accuracy: 0.7567, Val Loss: 1.2579, Val Accuracy: 0.6473
Epoch 4698/10000, Train Loss: 1.1666, Train Accuracy: 0.7567, Val Loss: 1.2578, Val Accuracy: 0.6473
Epoch 4699/10000, Train Loss: 1.1800, Train Accuracy: 0.7366, Val Loss: 1.2578, Val Accuracy: 0.6429
Epoch 4700/10000, Train Loss: 1.1809, Train Accuracy: 0.7321, Val Loss: 1.2578, Val Accuracy: 0.6429
Epoch 4701/10000, Train Loss: 1.1745, Train Accuracy: 0.7545, Val Loss: 1.2577, Val Accuracy: 0.6429
Epoch 4702/10000, Train Loss: 1.1726, Train Accuracy: 0.7444, Val Loss: 1.2577, Val Accuracy: 0.6384
Epoch 4703/10000, Train Loss: 1.1878, Train Accuracy: 0.7210, Val Loss: 1.2575, Val Accuracy: 0.6384
Epoch 4704/10000, Train Loss: 1.1899, Train Accuracy: 0.7266, Val Loss: 1.2576, Val Accuracy: 0.6384
Epoch 4705/10000, Train Loss: 1.1892, Train Accuracy: 0.7221, Val Loss: 1.2576, Val Accuracy: 0.6429
Epoch 4706/10000, Train Loss: 1.1885, Train Accuracy: 0.7366, Val Loss: 1.2575, Val Accuracy: 0.6473
Epoch 4707/10000, Train Loss: 1.1690, Train Accuracy: 0.7455, Val Loss: 1.2575, Val Accuracy: 0.6473
Epoch 4708/10000, Train Loss: 1.1785, Train Accuracy: 0.7388, Val Loss: 1.2576, Val Accuracy: 0.6473
Epoch 4709/10000, Train Loss: 1.1767, Train Accuracy: 0.7411, Val Loss: 1.2574, Val Accuracy: 0.6473
Epoch 4710/10000, Train Loss: 1.1854, Train Accuracy: 0.7333, Val Loss: 1.2575, Val Accuracy: 0.6473
Epoch 4711/10000, Train Loss: 1.1809, Train Accuracy: 0.7377, Val Loss: 1.2575, Val Accuracy: 0.6429
Epoch 4712/10000, Train Loss: 1.1741, Train Accuracy: 0.7422, Val Loss: 1.2574, Val Accuracy: 0.6384
Epoch 4713/10000, Train Loss: 1.1700, Train Accuracy: 0.7467, Val Loss: 1.2573, Val Accuracy: 0.6384
Epoch 4714/10000, Train Loss: 1.1868, Train Accuracy: 0.7266, Val Loss: 1.2573, Val Accuracy: 0.6384
Epoch 4715/10000, Train Loss: 1.1788, Train Accuracy: 0.7377, Val Loss: 1.2572, Val Accuracy: 0.6384
Epoch 4716/10000, Train Loss: 1.1799, Train Accuracy: 0.7366, Val Loss: 1.2572, Val Accuracy: 0.6384
Epoch 4717/10000, Train Loss: 1.1762, Train Accuracy: 0.7366, Val Loss: 1.2570, Val Accuracy: 0.6429
Epoch 4718/10000, Train Loss: 1.1659, Train Accuracy: 0.7556, Val Loss: 1.2569, Val Accuracy: 0.6429
Epoch 4719/10000, Train Loss: 1.1696, Train Accuracy: 0.7411, Val Loss: 1.2569, Val Accuracy: 0.6429
Epoch 4720/10000, Train Loss: 1.1851, Train Accuracy: 0.7277, Val Loss: 1.2566, Val Accuracy: 0.6429
Epoch 4721/10000, Train Loss: 1.1762, Train Accuracy: 0.7433, Val Loss: 1.2566, Val Accuracy: 0.6384
Epoch 4722/10000, Train Loss: 1.1631, Train Accuracy: 0.7556, Val Loss: 1.2566, Val Accuracy: 0.6384
Epoch 4723/10000, Train Loss: 1.1864, Train Accuracy: 0.7299, Val Loss: 1.2566, Val Accuracy: 0.6429
Epoch 4724/10000, Train Loss: 1.1819, Train Accuracy: 0.7333, Val Loss: 1.2568, Val Accuracy: 0.6384
Epoch 4725/10000, Train Loss: 1.1837, Train Accuracy: 0.7321, Val Loss: 1.2566, Val Accuracy: 0.6429
Epoch 4726/10000, Train Loss: 1.1691, Train Accuracy: 0.7556, Val Loss: 1.2567, Val Accuracy: 0.6429
Epoch 4727/10000, Train Loss: 1.1697, Train Accuracy: 0.7511, Val Loss: 1.2567, Val Accuracy: 0.6384
Epoch 4728/10000, Train Loss: 1.1806, Train Accuracy: 0.7266, Val Loss: 1.2566, Val Accuracy: 0.6429
Epoch 4729/10000, Train Loss: 1.1848, Train Accuracy: 0.7355, Val Loss: 1.2564, Val Accuracy: 0.6473
Epoch 4730/10000, Train Loss: 1.1773, Train Accuracy: 0.7467, Val Loss: 1.2564, Val Accuracy: 0.6473
Epoch 4731/10000, Train Loss: 1.1790, Train Accuracy: 0.7377, Val Loss: 1.2561, Val Accuracy: 0.6518
Epoch 4732/10000, Train Loss: 1.1883, Train Accuracy: 0.7299, Val Loss: 1.2561, Val Accuracy: 0.6473
Epoch 4733/10000, Train Loss: 1.1847, Train Accuracy: 0.7366, Val Loss: 1.2561, Val Accuracy: 0.6473
Epoch 4734/10000, Train Loss: 1.1773, Train Accuracy: 0.7500, Val Loss: 1.2561, Val Accuracy: 0.6429
Epoch 4735/10000, Train Loss: 1.1901, Train Accuracy: 0.7266, Val Loss: 1.2561, Val Accuracy: 0.6429
Epoch 4736/10000, Train Loss: 1.1726, Train Accuracy: 0.7444, Val Loss: 1.2560, Val Accuracy: 0.6429
Epoch 4737/10000, Train Loss: 1.1723, Train Accuracy: 0.7388, Val Loss: 1.2560, Val Accuracy: 0.6429
Epoch 4738/10000, Train Loss: 1.1804, Train Accuracy: 0.7321, Val Loss: 1.2561, Val Accuracy: 0.6473
Epoch 4739/10000, Train Loss: 1.1892, Train Accuracy: 0.7277, Val Loss: 1.2561, Val Accuracy: 0.6473
Epoch 4740/10000, Train Loss: 1.1733, Train Accuracy: 0.7444, Val Loss: 1.2559, Val Accuracy: 0.6518
Epoch 4741/10000, Train Loss: 1.1876, Train Accuracy: 0.7243, Val Loss: 1.2558, Val Accuracy: 0.6518
Epoch 4742/10000, Train Loss: 1.1775, Train Accuracy: 0.7422, Val Loss: 1.2558, Val Accuracy: 0.6473
Epoch 4743/10000, Train Loss: 1.1779, Train Accuracy: 0.7321, Val Loss: 1.2557, Val Accuracy: 0.6473
Epoch 4744/10000, Train Loss: 1.1748, Train Accuracy: 0.7433, Val Loss: 1.2557, Val Accuracy: 0.6473
Epoch 4745/10000, Train Loss: 1.1941, Train Accuracy: 0.7199, Val Loss: 1.2557, Val Accuracy: 0.6473
Epoch 4746/10000, Train Loss: 1.1758, Train Accuracy: 0.7366, Val Loss: 1.2554, Val Accuracy: 0.6518
Epoch 4747/10000, Train Loss: 1.1725, Train Accuracy: 0.7433, Val Loss: 1.2554, Val Accuracy: 0.6518
Epoch 4748/10000, Train Loss: 1.1815, Train Accuracy: 0.7344, Val Loss: 1.2553, Val Accuracy: 0.6473
Epoch 4749/10000, Train Loss: 1.1798, Train Accuracy: 0.7355, Val Loss: 1.2554, Val Accuracy: 0.6429
Epoch 4750/10000, Train Loss: 1.1811, Train Accuracy: 0.7444, Val Loss: 1.2556, Val Accuracy: 0.6429
Epoch 4751/10000, Train Loss: 1.1878, Train Accuracy: 0.7176, Val Loss: 1.2555, Val Accuracy: 0.6518
Epoch 4752/10000, Train Loss: 1.1869, Train Accuracy: 0.7333, Val Loss: 1.2554, Val Accuracy: 0.6518
Epoch 4753/10000, Train Loss: 1.1771, Train Accuracy: 0.7388, Val Loss: 1.2555, Val Accuracy: 0.6473
Epoch 4754/10000, Train Loss: 1.1846, Train Accuracy: 0.7243, Val Loss: 1.2552, Val Accuracy: 0.6473
Epoch 4755/10000, Train Loss: 1.1729, Train Accuracy: 0.7489, Val Loss: 1.2551, Val Accuracy: 0.6518
Epoch 4756/10000, Train Loss: 1.1769, Train Accuracy: 0.7310, Val Loss: 1.2550, Val Accuracy: 0.6518
Epoch 4757/10000, Train Loss: 1.1789, Train Accuracy: 0.7310, Val Loss: 1.2551, Val Accuracy: 0.6518
Epoch 4758/10000, Train Loss: 1.1770, Train Accuracy: 0.7388, Val Loss: 1.2549, Val Accuracy: 0.6562
Epoch 4759/10000, Train Loss: 1.1656, Train Accuracy: 0.7511, Val Loss: 1.2547, Val Accuracy: 0.6518
Epoch 4760/10000, Train Loss: 1.1745, Train Accuracy: 0.7455, Val Loss: 1.2547, Val Accuracy: 0.6518
Epoch 4761/10000, Train Loss: 1.1669, Train Accuracy: 0.7511, Val Loss: 1.2548, Val Accuracy: 0.6473
Epoch 4762/10000, Train Loss: 1.1619, Train Accuracy: 0.7511, Val Loss: 1.2549, Val Accuracy: 0.6473
Epoch 4763/10000, Train Loss: 1.1813, Train Accuracy: 0.7388, Val Loss: 1.2550, Val Accuracy: 0.6473
Epoch 4764/10000, Train Loss: 1.1757, Train Accuracy: 0.7433, Val Loss: 1.2549, Val Accuracy: 0.6473
Epoch 4765/10000, Train Loss: 1.1789, Train Accuracy: 0.7377, Val Loss: 1.2550, Val Accuracy: 0.6473
Epoch 4766/10000, Train Loss: 1.1764, Train Accuracy: 0.7377, Val Loss: 1.2550, Val Accuracy: 0.6473
Epoch 4767/10000, Train Loss: 1.1779, Train Accuracy: 0.7377, Val Loss: 1.2549, Val Accuracy: 0.6562
Epoch 4768/10000, Train Loss: 1.1676, Train Accuracy: 0.7511, Val Loss: 1.2550, Val Accuracy: 0.6562
Epoch 4769/10000, Train Loss: 1.1724, Train Accuracy: 0.7511, Val Loss: 1.2549, Val Accuracy: 0.6562
Epoch 4770/10000, Train Loss: 1.1890, Train Accuracy: 0.7221, Val Loss: 1.2547, Val Accuracy: 0.6607
Epoch 4771/10000, Train Loss: 1.1762, Train Accuracy: 0.7511, Val Loss: 1.2545, Val Accuracy: 0.6562
Epoch 4772/10000, Train Loss: 1.1693, Train Accuracy: 0.7522, Val Loss: 1.2545, Val Accuracy: 0.6518
Epoch 4773/10000, Train Loss: 1.1639, Train Accuracy: 0.7623, Val Loss: 1.2545, Val Accuracy: 0.6562
Epoch 4774/10000, Train Loss: 1.1679, Train Accuracy: 0.7478, Val Loss: 1.2546, Val Accuracy: 0.6518
Epoch 4775/10000, Train Loss: 1.1897, Train Accuracy: 0.7221, Val Loss: 1.2545, Val Accuracy: 0.6518
Epoch 4776/10000, Train Loss: 1.1660, Train Accuracy: 0.7589, Val Loss: 1.2546, Val Accuracy: 0.6562
Epoch 4777/10000, Train Loss: 1.1789, Train Accuracy: 0.7355, Val Loss: 1.2544, Val Accuracy: 0.6562
Epoch 4778/10000, Train Loss: 1.1785, Train Accuracy: 0.7344, Val Loss: 1.2543, Val Accuracy: 0.6562
Epoch 4779/10000, Train Loss: 1.1715, Train Accuracy: 0.7455, Val Loss: 1.2541, Val Accuracy: 0.6607
Epoch 4780/10000, Train Loss: 1.1713, Train Accuracy: 0.7444, Val Loss: 1.2542, Val Accuracy: 0.6518
Epoch 4781/10000, Train Loss: 1.1765, Train Accuracy: 0.7478, Val Loss: 1.2541, Val Accuracy: 0.6562
Epoch 4782/10000, Train Loss: 1.1640, Train Accuracy: 0.7567, Val Loss: 1.2540, Val Accuracy: 0.6562
Epoch 4783/10000, Train Loss: 1.1786, Train Accuracy: 0.7333, Val Loss: 1.2540, Val Accuracy: 0.6562
Epoch 4784/10000, Train Loss: 1.1700, Train Accuracy: 0.7511, Val Loss: 1.2539, Val Accuracy: 0.6518
Epoch 4785/10000, Train Loss: 1.1706, Train Accuracy: 0.7511, Val Loss: 1.2538, Val Accuracy: 0.6518
Epoch 4786/10000, Train Loss: 1.1680, Train Accuracy: 0.7489, Val Loss: 1.2537, Val Accuracy: 0.6473
Epoch 4787/10000, Train Loss: 1.1762, Train Accuracy: 0.7355, Val Loss: 1.2538, Val Accuracy: 0.6518
Epoch 4788/10000, Train Loss: 1.1700, Train Accuracy: 0.7467, Val Loss: 1.2538, Val Accuracy: 0.6518
Epoch 4789/10000, Train Loss: 1.1631, Train Accuracy: 0.7545, Val Loss: 1.2537, Val Accuracy: 0.6518
Epoch 4790/10000, Train Loss: 1.1765, Train Accuracy: 0.7478, Val Loss: 1.2535, Val Accuracy: 0.6473
Epoch 4791/10000, Train Loss: 1.1779, Train Accuracy: 0.7400, Val Loss: 1.2534, Val Accuracy: 0.6473
Epoch 4792/10000, Train Loss: 1.1722, Train Accuracy: 0.7411, Val Loss: 1.2535, Val Accuracy: 0.6518
Epoch 4793/10000, Train Loss: 1.1724, Train Accuracy: 0.7377, Val Loss: 1.2538, Val Accuracy: 0.6429
Epoch 4794/10000, Train Loss: 1.1741, Train Accuracy: 0.7400, Val Loss: 1.2537, Val Accuracy: 0.6429
Epoch 4795/10000, Train Loss: 1.1614, Train Accuracy: 0.7679, Val Loss: 1.2535, Val Accuracy: 0.6429
Epoch 4796/10000, Train Loss: 1.1699, Train Accuracy: 0.7467, Val Loss: 1.2536, Val Accuracy: 0.6429
Epoch 4797/10000, Train Loss: 1.1860, Train Accuracy: 0.7221, Val Loss: 1.2537, Val Accuracy: 0.6518
Epoch 4798/10000, Train Loss: 1.1663, Train Accuracy: 0.7444, Val Loss: 1.2536, Val Accuracy: 0.6518
Epoch 4799/10000, Train Loss: 1.1660, Train Accuracy: 0.7612, Val Loss: 1.2537, Val Accuracy: 0.6429
Epoch 4800/10000, Train Loss: 1.1726, Train Accuracy: 0.7411, Val Loss: 1.2537, Val Accuracy: 0.6473
Epoch 4801/10000, Train Loss: 1.1753, Train Accuracy: 0.7321, Val Loss: 1.2536, Val Accuracy: 0.6473
Epoch 4802/10000, Train Loss: 1.1659, Train Accuracy: 0.7511, Val Loss: 1.2536, Val Accuracy: 0.6473
Epoch 4803/10000, Train Loss: 1.1722, Train Accuracy: 0.7455, Val Loss: 1.2533, Val Accuracy: 0.6473
Epoch 4804/10000, Train Loss: 1.1769, Train Accuracy: 0.7400, Val Loss: 1.2531, Val Accuracy: 0.6473
Epoch 4805/10000, Train Loss: 1.1829, Train Accuracy: 0.7310, Val Loss: 1.2530, Val Accuracy: 0.6473
Epoch 4806/10000, Train Loss: 1.1804, Train Accuracy: 0.7288, Val Loss: 1.2529, Val Accuracy: 0.6473
Epoch 4807/10000, Train Loss: 1.1713, Train Accuracy: 0.7556, Val Loss: 1.2528, Val Accuracy: 0.6473
Epoch 4808/10000, Train Loss: 1.1862, Train Accuracy: 0.7210, Val Loss: 1.2527, Val Accuracy: 0.6518
Epoch 4809/10000, Train Loss: 1.1751, Train Accuracy: 0.7422, Val Loss: 1.2526, Val Accuracy: 0.6562
Epoch 4810/10000, Train Loss: 1.1769, Train Accuracy: 0.7467, Val Loss: 1.2527, Val Accuracy: 0.6518
Epoch 4811/10000, Train Loss: 1.1887, Train Accuracy: 0.7243, Val Loss: 1.2524, Val Accuracy: 0.6562
Epoch 4812/10000, Train Loss: 1.1845, Train Accuracy: 0.7344, Val Loss: 1.2523, Val Accuracy: 0.6518
Epoch 4813/10000, Train Loss: 1.1663, Train Accuracy: 0.7388, Val Loss: 1.2524, Val Accuracy: 0.6518
Epoch 4814/10000, Train Loss: 1.1786, Train Accuracy: 0.7321, Val Loss: 1.2524, Val Accuracy: 0.6518
Epoch 4815/10000, Train Loss: 1.1727, Train Accuracy: 0.7400, Val Loss: 1.2524, Val Accuracy: 0.6518
Epoch 4816/10000, Train Loss: 1.1729, Train Accuracy: 0.7455, Val Loss: 1.2523, Val Accuracy: 0.6562
Epoch 4817/10000, Train Loss: 1.1739, Train Accuracy: 0.7400, Val Loss: 1.2523, Val Accuracy: 0.6562
Epoch 4818/10000, Train Loss: 1.1735, Train Accuracy: 0.7455, Val Loss: 1.2522, Val Accuracy: 0.6562
Epoch 4819/10000, Train Loss: 1.1751, Train Accuracy: 0.7400, Val Loss: 1.2522, Val Accuracy: 0.6562
Epoch 4820/10000, Train Loss: 1.1698, Train Accuracy: 0.7500, Val Loss: 1.2520, Val Accuracy: 0.6607
Epoch 4821/10000, Train Loss: 1.1664, Train Accuracy: 0.7578, Val Loss: 1.2520, Val Accuracy: 0.6562
Epoch 4822/10000, Train Loss: 1.1751, Train Accuracy: 0.7433, Val Loss: 1.2521, Val Accuracy: 0.6518
Epoch 4823/10000, Train Loss: 1.1645, Train Accuracy: 0.7522, Val Loss: 1.2520, Val Accuracy: 0.6562
Epoch 4824/10000, Train Loss: 1.1726, Train Accuracy: 0.7422, Val Loss: 1.2521, Val Accuracy: 0.6562
Epoch 4825/10000, Train Loss: 1.1664, Train Accuracy: 0.7511, Val Loss: 1.2518, Val Accuracy: 0.6562
Epoch 4826/10000, Train Loss: 1.1661, Train Accuracy: 0.7455, Val Loss: 1.2517, Val Accuracy: 0.6562
Epoch 4827/10000, Train Loss: 1.1805, Train Accuracy: 0.7366, Val Loss: 1.2514, Val Accuracy: 0.6562
Epoch 4828/10000, Train Loss: 1.1642, Train Accuracy: 0.7578, Val Loss: 1.2513, Val Accuracy: 0.6562
Epoch 4829/10000, Train Loss: 1.1740, Train Accuracy: 0.7444, Val Loss: 1.2512, Val Accuracy: 0.6562
Epoch 4830/10000, Train Loss: 1.1598, Train Accuracy: 0.7612, Val Loss: 1.2511, Val Accuracy: 0.6607
Epoch 4831/10000, Train Loss: 1.1886, Train Accuracy: 0.7277, Val Loss: 1.2511, Val Accuracy: 0.6562
Epoch 4832/10000, Train Loss: 1.1700, Train Accuracy: 0.7511, Val Loss: 1.2510, Val Accuracy: 0.6562
Epoch 4833/10000, Train Loss: 1.1701, Train Accuracy: 0.7455, Val Loss: 1.2508, Val Accuracy: 0.6607
Epoch 4834/10000, Train Loss: 1.1759, Train Accuracy: 0.7455, Val Loss: 1.2509, Val Accuracy: 0.6607
Epoch 4835/10000, Train Loss: 1.1759, Train Accuracy: 0.7377, Val Loss: 1.2508, Val Accuracy: 0.6607
Epoch 4836/10000, Train Loss: 1.1709, Train Accuracy: 0.7478, Val Loss: 1.2507, Val Accuracy: 0.6607
Epoch 4837/10000, Train Loss: 1.1729, Train Accuracy: 0.7355, Val Loss: 1.2509, Val Accuracy: 0.6518
Epoch 4838/10000, Train Loss: 1.1768, Train Accuracy: 0.7411, Val Loss: 1.2508, Val Accuracy: 0.6562
Epoch 4839/10000, Train Loss: 1.1733, Train Accuracy: 0.7467, Val Loss: 1.2510, Val Accuracy: 0.6562
Epoch 4840/10000, Train Loss: 1.1696, Train Accuracy: 0.7411, Val Loss: 1.2510, Val Accuracy: 0.6562
Epoch 4841/10000, Train Loss: 1.1722, Train Accuracy: 0.7422, Val Loss: 1.2511, Val Accuracy: 0.6562
Epoch 4842/10000, Train Loss: 1.1725, Train Accuracy: 0.7455, Val Loss: 1.2508, Val Accuracy: 0.6562
Epoch 4843/10000, Train Loss: 1.1668, Train Accuracy: 0.7567, Val Loss: 1.2508, Val Accuracy: 0.6518
Epoch 4844/10000, Train Loss: 1.1668, Train Accuracy: 0.7533, Val Loss: 1.2506, Val Accuracy: 0.6518
Epoch 4845/10000, Train Loss: 1.1599, Train Accuracy: 0.7645, Val Loss: 1.2506, Val Accuracy: 0.6518
Epoch 4846/10000, Train Loss: 1.1715, Train Accuracy: 0.7411, Val Loss: 1.2507, Val Accuracy: 0.6562
Epoch 4847/10000, Train Loss: 1.1788, Train Accuracy: 0.7288, Val Loss: 1.2508, Val Accuracy: 0.6562
Epoch 4848/10000, Train Loss: 1.1755, Train Accuracy: 0.7411, Val Loss: 1.2508, Val Accuracy: 0.6562
Epoch 4849/10000, Train Loss: 1.1809, Train Accuracy: 0.7266, Val Loss: 1.2507, Val Accuracy: 0.6607
Epoch 4850/10000, Train Loss: 1.1684, Train Accuracy: 0.7444, Val Loss: 1.2504, Val Accuracy: 0.6607
Epoch 4851/10000, Train Loss: 1.1732, Train Accuracy: 0.7400, Val Loss: 1.2505, Val Accuracy: 0.6562
Epoch 4852/10000, Train Loss: 1.1640, Train Accuracy: 0.7556, Val Loss: 1.2504, Val Accuracy: 0.6562
Epoch 4853/10000, Train Loss: 1.1747, Train Accuracy: 0.7522, Val Loss: 1.2505, Val Accuracy: 0.6518
Epoch 4854/10000, Train Loss: 1.1749, Train Accuracy: 0.7433, Val Loss: 1.2502, Val Accuracy: 0.6562
Epoch 4855/10000, Train Loss: 1.1653, Train Accuracy: 0.7623, Val Loss: 1.2500, Val Accuracy: 0.6562
Epoch 4856/10000, Train Loss: 1.1731, Train Accuracy: 0.7444, Val Loss: 1.2500, Val Accuracy: 0.6518
Epoch 4857/10000, Train Loss: 1.1759, Train Accuracy: 0.7333, Val Loss: 1.2500, Val Accuracy: 0.6518
Epoch 4858/10000, Train Loss: 1.1715, Train Accuracy: 0.7433, Val Loss: 1.2501, Val Accuracy: 0.6562
Epoch 4859/10000, Train Loss: 1.1667, Train Accuracy: 0.7478, Val Loss: 1.2501, Val Accuracy: 0.6562
Epoch 4860/10000, Train Loss: 1.1679, Train Accuracy: 0.7467, Val Loss: 1.2500, Val Accuracy: 0.6562
Epoch 4861/10000, Train Loss: 1.1701, Train Accuracy: 0.7511, Val Loss: 1.2500, Val Accuracy: 0.6562
Epoch 4862/10000, Train Loss: 1.1629, Train Accuracy: 0.7522, Val Loss: 1.2499, Val Accuracy: 0.6562
Epoch 4863/10000, Train Loss: 1.1818, Train Accuracy: 0.7243, Val Loss: 1.2497, Val Accuracy: 0.6562
Epoch 4864/10000, Train Loss: 1.1540, Train Accuracy: 0.7656, Val Loss: 1.2495, Val Accuracy: 0.6518
Epoch 4865/10000, Train Loss: 1.1674, Train Accuracy: 0.7522, Val Loss: 1.2494, Val Accuracy: 0.6518
Epoch 4866/10000, Train Loss: 1.1808, Train Accuracy: 0.7344, Val Loss: 1.2494, Val Accuracy: 0.6518
Epoch 4867/10000, Train Loss: 1.1803, Train Accuracy: 0.7355, Val Loss: 1.2493, Val Accuracy: 0.6518
Epoch 4868/10000, Train Loss: 1.1726, Train Accuracy: 0.7411, Val Loss: 1.2493, Val Accuracy: 0.6562
Epoch 4869/10000, Train Loss: 1.1661, Train Accuracy: 0.7478, Val Loss: 1.2495, Val Accuracy: 0.6562
Epoch 4870/10000, Train Loss: 1.1740, Train Accuracy: 0.7500, Val Loss: 1.2494, Val Accuracy: 0.6562
Epoch 4871/10000, Train Loss: 1.1739, Train Accuracy: 0.7344, Val Loss: 1.2492, Val Accuracy: 0.6562
Epoch 4872/10000, Train Loss: 1.1727, Train Accuracy: 0.7467, Val Loss: 1.2493, Val Accuracy: 0.6562
Epoch 4873/10000, Train Loss: 1.1691, Train Accuracy: 0.7422, Val Loss: 1.2492, Val Accuracy: 0.6562
Epoch 4874/10000, Train Loss: 1.1671, Train Accuracy: 0.7455, Val Loss: 1.2490, Val Accuracy: 0.6607
Epoch 4875/10000, Train Loss: 1.1728, Train Accuracy: 0.7489, Val Loss: 1.2490, Val Accuracy: 0.6607
Epoch 4876/10000, Train Loss: 1.1637, Train Accuracy: 0.7522, Val Loss: 1.2489, Val Accuracy: 0.6607
Epoch 4877/10000, Train Loss: 1.1626, Train Accuracy: 0.7545, Val Loss: 1.2487, Val Accuracy: 0.6607
Epoch 4878/10000, Train Loss: 1.1631, Train Accuracy: 0.7612, Val Loss: 1.2485, Val Accuracy: 0.6562
Epoch 4879/10000, Train Loss: 1.1672, Train Accuracy: 0.7467, Val Loss: 1.2485, Val Accuracy: 0.6652
Epoch 4880/10000, Train Loss: 1.1661, Train Accuracy: 0.7489, Val Loss: 1.2484, Val Accuracy: 0.6652
Epoch 4881/10000, Train Loss: 1.1708, Train Accuracy: 0.7489, Val Loss: 1.2485, Val Accuracy: 0.6607
Epoch 4882/10000, Train Loss: 1.1696, Train Accuracy: 0.7455, Val Loss: 1.2485, Val Accuracy: 0.6562
Epoch 4883/10000, Train Loss: 1.1599, Train Accuracy: 0.7589, Val Loss: 1.2485, Val Accuracy: 0.6562
Epoch 4884/10000, Train Loss: 1.1641, Train Accuracy: 0.7478, Val Loss: 1.2485, Val Accuracy: 0.6562
Epoch 4885/10000, Train Loss: 1.1769, Train Accuracy: 0.7266, Val Loss: 1.2485, Val Accuracy: 0.6562
Epoch 4886/10000, Train Loss: 1.1716, Train Accuracy: 0.7500, Val Loss: 1.2484, Val Accuracy: 0.6562
Epoch 4887/10000, Train Loss: 1.1750, Train Accuracy: 0.7511, Val Loss: 1.2482, Val Accuracy: 0.6562
Epoch 4888/10000, Train Loss: 1.1733, Train Accuracy: 0.7455, Val Loss: 1.2482, Val Accuracy: 0.6562
Epoch 4889/10000, Train Loss: 1.1606, Train Accuracy: 0.7600, Val Loss: 1.2479, Val Accuracy: 0.6607
Epoch 4890/10000, Train Loss: 1.1659, Train Accuracy: 0.7522, Val Loss: 1.2478, Val Accuracy: 0.6607
Epoch 4891/10000, Train Loss: 1.1742, Train Accuracy: 0.7411, Val Loss: 1.2479, Val Accuracy: 0.6652
Epoch 4892/10000, Train Loss: 1.1594, Train Accuracy: 0.7634, Val Loss: 1.2478, Val Accuracy: 0.6562
Epoch 4893/10000, Train Loss: 1.1613, Train Accuracy: 0.7511, Val Loss: 1.2478, Val Accuracy: 0.6607
Epoch 4894/10000, Train Loss: 1.1672, Train Accuracy: 0.7567, Val Loss: 1.2478, Val Accuracy: 0.6652
Epoch 4895/10000, Train Loss: 1.1739, Train Accuracy: 0.7400, Val Loss: 1.2477, Val Accuracy: 0.6652
Epoch 4896/10000, Train Loss: 1.1602, Train Accuracy: 0.7634, Val Loss: 1.2476, Val Accuracy: 0.6652
Epoch 4897/10000, Train Loss: 1.1634, Train Accuracy: 0.7511, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4898/10000, Train Loss: 1.1664, Train Accuracy: 0.7511, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4899/10000, Train Loss: 1.1607, Train Accuracy: 0.7589, Val Loss: 1.2476, Val Accuracy: 0.6652
Epoch 4900/10000, Train Loss: 1.1718, Train Accuracy: 0.7556, Val Loss: 1.2476, Val Accuracy: 0.6652
Epoch 4901/10000, Train Loss: 1.1693, Train Accuracy: 0.7489, Val Loss: 1.2476, Val Accuracy: 0.6652
Epoch 4902/10000, Train Loss: 1.1629, Train Accuracy: 0.7489, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4903/10000, Train Loss: 1.1734, Train Accuracy: 0.7377, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4904/10000, Train Loss: 1.1760, Train Accuracy: 0.7400, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4905/10000, Train Loss: 1.1714, Train Accuracy: 0.7400, Val Loss: 1.2475, Val Accuracy: 0.6652
Epoch 4906/10000, Train Loss: 1.1743, Train Accuracy: 0.7467, Val Loss: 1.2477, Val Accuracy: 0.6652
Epoch 4907/10000, Train Loss: 1.1669, Train Accuracy: 0.7467, Val Loss: 1.2477, Val Accuracy: 0.6652
Epoch 4908/10000, Train Loss: 1.1670, Train Accuracy: 0.7589, Val Loss: 1.2478, Val Accuracy: 0.6652
Epoch 4909/10000, Train Loss: 1.1779, Train Accuracy: 0.7366, Val Loss: 1.2478, Val Accuracy: 0.6607
Epoch 4910/10000, Train Loss: 1.1692, Train Accuracy: 0.7511, Val Loss: 1.2478, Val Accuracy: 0.6607
Epoch 4911/10000, Train Loss: 1.1755, Train Accuracy: 0.7344, Val Loss: 1.2478, Val Accuracy: 0.6652
Epoch 4912/10000, Train Loss: 1.1631, Train Accuracy: 0.7545, Val Loss: 1.2479, Val Accuracy: 0.6607
Epoch 4913/10000, Train Loss: 1.1698, Train Accuracy: 0.7411, Val Loss: 1.2478, Val Accuracy: 0.6562
Epoch 4914/10000, Train Loss: 1.1745, Train Accuracy: 0.7310, Val Loss: 1.2477, Val Accuracy: 0.6607
Epoch 4915/10000, Train Loss: 1.1657, Train Accuracy: 0.7500, Val Loss: 1.2477, Val Accuracy: 0.6562
Epoch 4916/10000, Train Loss: 1.1669, Train Accuracy: 0.7567, Val Loss: 1.2477, Val Accuracy: 0.6562
Epoch 4917/10000, Train Loss: 1.1747, Train Accuracy: 0.7366, Val Loss: 1.2477, Val Accuracy: 0.6562
Epoch 4918/10000, Train Loss: 1.1600, Train Accuracy: 0.7589, Val Loss: 1.2475, Val Accuracy: 0.6607
Epoch 4919/10000, Train Loss: 1.1789, Train Accuracy: 0.7333, Val Loss: 1.2474, Val Accuracy: 0.6607
Epoch 4920/10000, Train Loss: 1.1645, Train Accuracy: 0.7522, Val Loss: 1.2473, Val Accuracy: 0.6652
Epoch 4921/10000, Train Loss: 1.1669, Train Accuracy: 0.7467, Val Loss: 1.2476, Val Accuracy: 0.6562
Epoch 4922/10000, Train Loss: 1.1690, Train Accuracy: 0.7489, Val Loss: 1.2474, Val Accuracy: 0.6607
Epoch 4923/10000, Train Loss: 1.1733, Train Accuracy: 0.7411, Val Loss: 1.2474, Val Accuracy: 0.6607
Epoch 4924/10000, Train Loss: 1.1540, Train Accuracy: 0.7522, Val Loss: 1.2474, Val Accuracy: 0.6607
Epoch 4925/10000, Train Loss: 1.1686, Train Accuracy: 0.7533, Val Loss: 1.2472, Val Accuracy: 0.6607
Epoch 4926/10000, Train Loss: 1.1584, Train Accuracy: 0.7612, Val Loss: 1.2471, Val Accuracy: 0.6652
Epoch 4927/10000, Train Loss: 1.1744, Train Accuracy: 0.7422, Val Loss: 1.2468, Val Accuracy: 0.6652
Epoch 4928/10000, Train Loss: 1.1771, Train Accuracy: 0.7299, Val Loss: 1.2468, Val Accuracy: 0.6652
Epoch 4929/10000, Train Loss: 1.1551, Train Accuracy: 0.7634, Val Loss: 1.2468, Val Accuracy: 0.6652
Epoch 4930/10000, Train Loss: 1.1748, Train Accuracy: 0.7400, Val Loss: 1.2468, Val Accuracy: 0.6652
Epoch 4931/10000, Train Loss: 1.1668, Train Accuracy: 0.7422, Val Loss: 1.2465, Val Accuracy: 0.6652
Epoch 4932/10000, Train Loss: 1.1644, Train Accuracy: 0.7511, Val Loss: 1.2465, Val Accuracy: 0.6652
Epoch 4933/10000, Train Loss: 1.1693, Train Accuracy: 0.7522, Val Loss: 1.2465, Val Accuracy: 0.6607
Epoch 4934/10000, Train Loss: 1.1661, Train Accuracy: 0.7489, Val Loss: 1.2467, Val Accuracy: 0.6607
Epoch 4935/10000, Train Loss: 1.1617, Train Accuracy: 0.7634, Val Loss: 1.2466, Val Accuracy: 0.6652
Epoch 4936/10000, Train Loss: 1.1672, Train Accuracy: 0.7511, Val Loss: 1.2465, Val Accuracy: 0.6652
Epoch 4937/10000, Train Loss: 1.1764, Train Accuracy: 0.7400, Val Loss: 1.2463, Val Accuracy: 0.6652
Epoch 4938/10000, Train Loss: 1.1585, Train Accuracy: 0.7567, Val Loss: 1.2464, Val Accuracy: 0.6652
Epoch 4939/10000, Train Loss: 1.1778, Train Accuracy: 0.7344, Val Loss: 1.2463, Val Accuracy: 0.6652
Epoch 4940/10000, Train Loss: 1.1744, Train Accuracy: 0.7444, Val Loss: 1.2463, Val Accuracy: 0.6607
Epoch 4941/10000, Train Loss: 1.1697, Train Accuracy: 0.7455, Val Loss: 1.2464, Val Accuracy: 0.6652
Epoch 4942/10000, Train Loss: 1.1618, Train Accuracy: 0.7556, Val Loss: 1.2462, Val Accuracy: 0.6696
Epoch 4943/10000, Train Loss: 1.1589, Train Accuracy: 0.7567, Val Loss: 1.2461, Val Accuracy: 0.6652
Epoch 4944/10000, Train Loss: 1.1506, Train Accuracy: 0.7634, Val Loss: 1.2460, Val Accuracy: 0.6652
Epoch 4945/10000, Train Loss: 1.1505, Train Accuracy: 0.7712, Val Loss: 1.2461, Val Accuracy: 0.6696
Epoch 4946/10000, Train Loss: 1.1665, Train Accuracy: 0.7589, Val Loss: 1.2461, Val Accuracy: 0.6652
Epoch 4947/10000, Train Loss: 1.1681, Train Accuracy: 0.7545, Val Loss: 1.2461, Val Accuracy: 0.6652
Epoch 4948/10000, Train Loss: 1.1748, Train Accuracy: 0.7377, Val Loss: 1.2461, Val Accuracy: 0.6652
Epoch 4949/10000, Train Loss: 1.1600, Train Accuracy: 0.7612, Val Loss: 1.2461, Val Accuracy: 0.6696
Epoch 4950/10000, Train Loss: 1.1688, Train Accuracy: 0.7489, Val Loss: 1.2458, Val Accuracy: 0.6696
Epoch 4951/10000, Train Loss: 1.1703, Train Accuracy: 0.7467, Val Loss: 1.2457, Val Accuracy: 0.6696
Epoch 4952/10000, Train Loss: 1.1628, Train Accuracy: 0.7656, Val Loss: 1.2455, Val Accuracy: 0.6696
Epoch 4953/10000, Train Loss: 1.1587, Train Accuracy: 0.7634, Val Loss: 1.2455, Val Accuracy: 0.6696
Epoch 4954/10000, Train Loss: 1.1577, Train Accuracy: 0.7589, Val Loss: 1.2453, Val Accuracy: 0.6696
Epoch 4955/10000, Train Loss: 1.1556, Train Accuracy: 0.7623, Val Loss: 1.2452, Val Accuracy: 0.6696
Epoch 4956/10000, Train Loss: 1.1643, Train Accuracy: 0.7556, Val Loss: 1.2453, Val Accuracy: 0.6696
Epoch 4957/10000, Train Loss: 1.1739, Train Accuracy: 0.7433, Val Loss: 1.2453, Val Accuracy: 0.6696
Epoch 4958/10000, Train Loss: 1.1674, Train Accuracy: 0.7478, Val Loss: 1.2453, Val Accuracy: 0.6696
Epoch 4959/10000, Train Loss: 1.1650, Train Accuracy: 0.7589, Val Loss: 1.2452, Val Accuracy: 0.6696
Epoch 4960/10000, Train Loss: 1.1726, Train Accuracy: 0.7511, Val Loss: 1.2452, Val Accuracy: 0.6696
Epoch 4961/10000, Train Loss: 1.1717, Train Accuracy: 0.7377, Val Loss: 1.2454, Val Accuracy: 0.6696
Epoch 4962/10000, Train Loss: 1.1818, Train Accuracy: 0.7344, Val Loss: 1.2452, Val Accuracy: 0.6696
Epoch 4963/10000, Train Loss: 1.1713, Train Accuracy: 0.7511, Val Loss: 1.2452, Val Accuracy: 0.6652
Epoch 4964/10000, Train Loss: 1.1600, Train Accuracy: 0.7612, Val Loss: 1.2452, Val Accuracy: 0.6652
Epoch 4965/10000, Train Loss: 1.1767, Train Accuracy: 0.7422, Val Loss: 1.2452, Val Accuracy: 0.6696
Epoch 4966/10000, Train Loss: 1.1675, Train Accuracy: 0.7422, Val Loss: 1.2451, Val Accuracy: 0.6696
Epoch 4967/10000, Train Loss: 1.1565, Train Accuracy: 0.7545, Val Loss: 1.2451, Val Accuracy: 0.6696
Epoch 4968/10000, Train Loss: 1.1638, Train Accuracy: 0.7500, Val Loss: 1.2449, Val Accuracy: 0.6696
Epoch 4969/10000, Train Loss: 1.1547, Train Accuracy: 0.7623, Val Loss: 1.2450, Val Accuracy: 0.6696
Epoch 4970/10000, Train Loss: 1.1734, Train Accuracy: 0.7355, Val Loss: 1.2450, Val Accuracy: 0.6696
Epoch 4971/10000, Train Loss: 1.1712, Train Accuracy: 0.7467, Val Loss: 1.2449, Val Accuracy: 0.6696
Epoch 4972/10000, Train Loss: 1.1793, Train Accuracy: 0.7344, Val Loss: 1.2448, Val Accuracy: 0.6696
Epoch 4973/10000, Train Loss: 1.1690, Train Accuracy: 0.7522, Val Loss: 1.2449, Val Accuracy: 0.6696
Epoch 4974/10000, Train Loss: 1.1657, Train Accuracy: 0.7444, Val Loss: 1.2448, Val Accuracy: 0.6696
Epoch 4975/10000, Train Loss: 1.1616, Train Accuracy: 0.7567, Val Loss: 1.2447, Val Accuracy: 0.6696
Epoch 4976/10000, Train Loss: 1.1630, Train Accuracy: 0.7478, Val Loss: 1.2446, Val Accuracy: 0.6696
Epoch 4977/10000, Train Loss: 1.1691, Train Accuracy: 0.7478, Val Loss: 1.2446, Val Accuracy: 0.6652
Epoch 4978/10000, Train Loss: 1.1732, Train Accuracy: 0.7489, Val Loss: 1.2448, Val Accuracy: 0.6652
Epoch 4979/10000, Train Loss: 1.1595, Train Accuracy: 0.7623, Val Loss: 1.2446, Val Accuracy: 0.6652
Epoch 4980/10000, Train Loss: 1.1672, Train Accuracy: 0.7455, Val Loss: 1.2442, Val Accuracy: 0.6696
Epoch 4981/10000, Train Loss: 1.1647, Train Accuracy: 0.7623, Val Loss: 1.2441, Val Accuracy: 0.6741
Epoch 4982/10000, Train Loss: 1.1639, Train Accuracy: 0.7444, Val Loss: 1.2442, Val Accuracy: 0.6741
Epoch 4983/10000, Train Loss: 1.1680, Train Accuracy: 0.7444, Val Loss: 1.2441, Val Accuracy: 0.6741
Epoch 4984/10000, Train Loss: 1.1432, Train Accuracy: 0.7846, Val Loss: 1.2441, Val Accuracy: 0.6741
Epoch 4985/10000, Train Loss: 1.1674, Train Accuracy: 0.7478, Val Loss: 1.2441, Val Accuracy: 0.6741
Epoch 4986/10000, Train Loss: 1.1516, Train Accuracy: 0.7712, Val Loss: 1.2440, Val Accuracy: 0.6741
Epoch 4987/10000, Train Loss: 1.1805, Train Accuracy: 0.7254, Val Loss: 1.2439, Val Accuracy: 0.6741
Epoch 4988/10000, Train Loss: 1.1521, Train Accuracy: 0.7667, Val Loss: 1.2438, Val Accuracy: 0.6741
Epoch 4989/10000, Train Loss: 1.1681, Train Accuracy: 0.7478, Val Loss: 1.2438, Val Accuracy: 0.6741
Epoch 4990/10000, Train Loss: 1.1592, Train Accuracy: 0.7656, Val Loss: 1.2436, Val Accuracy: 0.6741
Epoch 4991/10000, Train Loss: 1.1748, Train Accuracy: 0.7489, Val Loss: 1.2434, Val Accuracy: 0.6741
Epoch 4992/10000, Train Loss: 1.1701, Train Accuracy: 0.7455, Val Loss: 1.2434, Val Accuracy: 0.6741
Epoch 4993/10000, Train Loss: 1.1775, Train Accuracy: 0.7511, Val Loss: 1.2433, Val Accuracy: 0.6741
Epoch 4994/10000, Train Loss: 1.1597, Train Accuracy: 0.7656, Val Loss: 1.2433, Val Accuracy: 0.6741
Epoch 4995/10000, Train Loss: 1.1592, Train Accuracy: 0.7612, Val Loss: 1.2432, Val Accuracy: 0.6741
Epoch 4996/10000, Train Loss: 1.1763, Train Accuracy: 0.7344, Val Loss: 1.2432, Val Accuracy: 0.6741
Epoch 4997/10000, Train Loss: 1.1617, Train Accuracy: 0.7600, Val Loss: 1.2431, Val Accuracy: 0.6741
Epoch 4998/10000, Train Loss: 1.1615, Train Accuracy: 0.7600, Val Loss: 1.2431, Val Accuracy: 0.6741
Epoch 4999/10000, Train Loss: 1.1623, Train Accuracy: 0.7556, Val Loss: 1.2431, Val Accuracy: 0.6741
Epoch 5000/10000, Train Loss: 1.1632, Train Accuracy: 0.7567, Val Loss: 1.2430, Val Accuracy: 0.6741
Epoch 5001/10000, Train Loss: 1.1579, Train Accuracy: 0.7623, Val Loss: 1.2429, Val Accuracy: 0.6741
Epoch 5002/10000, Train Loss: 1.1563, Train Accuracy: 0.7623, Val Loss: 1.2429, Val Accuracy: 0.6741
Epoch 5003/10000, Train Loss: 1.1518, Train Accuracy: 0.7746, Val Loss: 1.2428, Val Accuracy: 0.6741
Epoch 5004/10000, Train Loss: 1.1664, Train Accuracy: 0.7467, Val Loss: 1.2427, Val Accuracy: 0.6741
Epoch 5005/10000, Train Loss: 1.1655, Train Accuracy: 0.7511, Val Loss: 1.2427, Val Accuracy: 0.6741
Epoch 5006/10000, Train Loss: 1.1700, Train Accuracy: 0.7411, Val Loss: 1.2427, Val Accuracy: 0.6741
Epoch 5007/10000, Train Loss: 1.1716, Train Accuracy: 0.7433, Val Loss: 1.2428, Val Accuracy: 0.6741
Epoch 5008/10000, Train Loss: 1.1688, Train Accuracy: 0.7478, Val Loss: 1.2427, Val Accuracy: 0.6741
Epoch 5009/10000, Train Loss: 1.1606, Train Accuracy: 0.7511, Val Loss: 1.2427, Val Accuracy: 0.6741
Epoch 5010/10000, Train Loss: 1.1655, Train Accuracy: 0.7511, Val Loss: 1.2425, Val Accuracy: 0.6741
Epoch 5011/10000, Train Loss: 1.1675, Train Accuracy: 0.7455, Val Loss: 1.2424, Val Accuracy: 0.6741
Epoch 5012/10000, Train Loss: 1.1528, Train Accuracy: 0.7623, Val Loss: 1.2423, Val Accuracy: 0.6741
Epoch 5013/10000, Train Loss: 1.1657, Train Accuracy: 0.7500, Val Loss: 1.2425, Val Accuracy: 0.6741
Epoch 5014/10000, Train Loss: 1.1610, Train Accuracy: 0.7545, Val Loss: 1.2424, Val Accuracy: 0.6741
Epoch 5015/10000, Train Loss: 1.1491, Train Accuracy: 0.7734, Val Loss: 1.2422, Val Accuracy: 0.6741
Epoch 5016/10000, Train Loss: 1.1747, Train Accuracy: 0.7455, Val Loss: 1.2422, Val Accuracy: 0.6741
Epoch 5017/10000, Train Loss: 1.1699, Train Accuracy: 0.7467, Val Loss: 1.2421, Val Accuracy: 0.6741
Epoch 5018/10000, Train Loss: 1.1638, Train Accuracy: 0.7500, Val Loss: 1.2420, Val Accuracy: 0.6741
Epoch 5019/10000, Train Loss: 1.1598, Train Accuracy: 0.7589, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5020/10000, Train Loss: 1.1607, Train Accuracy: 0.7612, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5021/10000, Train Loss: 1.1559, Train Accuracy: 0.7634, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5022/10000, Train Loss: 1.1793, Train Accuracy: 0.7321, Val Loss: 1.2415, Val Accuracy: 0.6741
Epoch 5023/10000, Train Loss: 1.1745, Train Accuracy: 0.7388, Val Loss: 1.2415, Val Accuracy: 0.6741
Epoch 5024/10000, Train Loss: 1.1662, Train Accuracy: 0.7567, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5025/10000, Train Loss: 1.1635, Train Accuracy: 0.7612, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5026/10000, Train Loss: 1.1666, Train Accuracy: 0.7433, Val Loss: 1.2417, Val Accuracy: 0.6741
Epoch 5027/10000, Train Loss: 1.1568, Train Accuracy: 0.7679, Val Loss: 1.2417, Val Accuracy: 0.6741
Epoch 5028/10000, Train Loss: 1.1474, Train Accuracy: 0.7712, Val Loss: 1.2418, Val Accuracy: 0.6741
Epoch 5029/10000, Train Loss: 1.1577, Train Accuracy: 0.7589, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5030/10000, Train Loss: 1.1615, Train Accuracy: 0.7612, Val Loss: 1.2418, Val Accuracy: 0.6741
Epoch 5031/10000, Train Loss: 1.1538, Train Accuracy: 0.7734, Val Loss: 1.2418, Val Accuracy: 0.6696
Epoch 5032/10000, Train Loss: 1.1603, Train Accuracy: 0.7556, Val Loss: 1.2419, Val Accuracy: 0.6696
Epoch 5033/10000, Train Loss: 1.1719, Train Accuracy: 0.7467, Val Loss: 1.2417, Val Accuracy: 0.6696
Epoch 5034/10000, Train Loss: 1.1634, Train Accuracy: 0.7455, Val Loss: 1.2417, Val Accuracy: 0.6696
Epoch 5035/10000, Train Loss: 1.1532, Train Accuracy: 0.7623, Val Loss: 1.2418, Val Accuracy: 0.6696
Epoch 5036/10000, Train Loss: 1.1668, Train Accuracy: 0.7511, Val Loss: 1.2419, Val Accuracy: 0.6741
Epoch 5037/10000, Train Loss: 1.1702, Train Accuracy: 0.7455, Val Loss: 1.2419, Val Accuracy: 0.6741
Epoch 5038/10000, Train Loss: 1.1667, Train Accuracy: 0.7511, Val Loss: 1.2419, Val Accuracy: 0.6741
Epoch 5039/10000, Train Loss: 1.1694, Train Accuracy: 0.7388, Val Loss: 1.2416, Val Accuracy: 0.6786
Epoch 5040/10000, Train Loss: 1.1839, Train Accuracy: 0.7266, Val Loss: 1.2413, Val Accuracy: 0.6741
Epoch 5041/10000, Train Loss: 1.1601, Train Accuracy: 0.7511, Val Loss: 1.2415, Val Accuracy: 0.6741
Epoch 5042/10000, Train Loss: 1.1618, Train Accuracy: 0.7444, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5043/10000, Train Loss: 1.1597, Train Accuracy: 0.7533, Val Loss: 1.2415, Val Accuracy: 0.6741
Epoch 5044/10000, Train Loss: 1.1648, Train Accuracy: 0.7489, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5045/10000, Train Loss: 1.1573, Train Accuracy: 0.7545, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5046/10000, Train Loss: 1.1682, Train Accuracy: 0.7478, Val Loss: 1.2415, Val Accuracy: 0.6741
Epoch 5047/10000, Train Loss: 1.1714, Train Accuracy: 0.7366, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5048/10000, Train Loss: 1.1734, Train Accuracy: 0.7489, Val Loss: 1.2416, Val Accuracy: 0.6741
Epoch 5049/10000, Train Loss: 1.1766, Train Accuracy: 0.7310, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5050/10000, Train Loss: 1.1609, Train Accuracy: 0.7679, Val Loss: 1.2414, Val Accuracy: 0.6741
Epoch 5051/10000, Train Loss: 1.1627, Train Accuracy: 0.7533, Val Loss: 1.2410, Val Accuracy: 0.6741
Epoch 5052/10000, Train Loss: 1.1678, Train Accuracy: 0.7500, Val Loss: 1.2409, Val Accuracy: 0.6786
Epoch 5053/10000, Train Loss: 1.1703, Train Accuracy: 0.7533, Val Loss: 1.2410, Val Accuracy: 0.6786
Epoch 5054/10000, Train Loss: 1.1432, Train Accuracy: 0.7712, Val Loss: 1.2412, Val Accuracy: 0.6786
Epoch 5055/10000, Train Loss: 1.1652, Train Accuracy: 0.7467, Val Loss: 1.2409, Val Accuracy: 0.6786
Epoch 5056/10000, Train Loss: 1.1614, Train Accuracy: 0.7545, Val Loss: 1.2409, Val Accuracy: 0.6786
Epoch 5057/10000, Train Loss: 1.1537, Train Accuracy: 0.7556, Val Loss: 1.2409, Val Accuracy: 0.6830
Epoch 5058/10000, Train Loss: 1.1625, Train Accuracy: 0.7556, Val Loss: 1.2408, Val Accuracy: 0.6830
Epoch 5059/10000, Train Loss: 1.1633, Train Accuracy: 0.7467, Val Loss: 1.2407, Val Accuracy: 0.6830
Epoch 5060/10000, Train Loss: 1.1606, Train Accuracy: 0.7667, Val Loss: 1.2408, Val Accuracy: 0.6830
Epoch 5061/10000, Train Loss: 1.1669, Train Accuracy: 0.7411, Val Loss: 1.2407, Val Accuracy: 0.6830
Epoch 5062/10000, Train Loss: 1.1541, Train Accuracy: 0.7467, Val Loss: 1.2407, Val Accuracy: 0.6786
Epoch 5063/10000, Train Loss: 1.1681, Train Accuracy: 0.7411, Val Loss: 1.2407, Val Accuracy: 0.6830
Epoch 5064/10000, Train Loss: 1.1635, Train Accuracy: 0.7522, Val Loss: 1.2407, Val Accuracy: 0.6786
Epoch 5065/10000, Train Loss: 1.1595, Train Accuracy: 0.7533, Val Loss: 1.2405, Val Accuracy: 0.6741
Epoch 5066/10000, Train Loss: 1.1710, Train Accuracy: 0.7411, Val Loss: 1.2405, Val Accuracy: 0.6741
Epoch 5067/10000, Train Loss: 1.1651, Train Accuracy: 0.7589, Val Loss: 1.2404, Val Accuracy: 0.6741
Epoch 5068/10000, Train Loss: 1.1498, Train Accuracy: 0.7779, Val Loss: 1.2405, Val Accuracy: 0.6741
Epoch 5069/10000, Train Loss: 1.1650, Train Accuracy: 0.7478, Val Loss: 1.2404, Val Accuracy: 0.6741
Epoch 5070/10000, Train Loss: 1.1632, Train Accuracy: 0.7489, Val Loss: 1.2403, Val Accuracy: 0.6741
Epoch 5071/10000, Train Loss: 1.1712, Train Accuracy: 0.7545, Val Loss: 1.2401, Val Accuracy: 0.6741
Epoch 5072/10000, Train Loss: 1.1703, Train Accuracy: 0.7411, Val Loss: 1.2401, Val Accuracy: 0.6741
Epoch 5073/10000, Train Loss: 1.1458, Train Accuracy: 0.7768, Val Loss: 1.2401, Val Accuracy: 0.6741
Epoch 5074/10000, Train Loss: 1.1631, Train Accuracy: 0.7545, Val Loss: 1.2401, Val Accuracy: 0.6741
Epoch 5075/10000, Train Loss: 1.1614, Train Accuracy: 0.7500, Val Loss: 1.2400, Val Accuracy: 0.6741
Epoch 5076/10000, Train Loss: 1.1650, Train Accuracy: 0.7556, Val Loss: 1.2401, Val Accuracy: 0.6786
Epoch 5077/10000, Train Loss: 1.1647, Train Accuracy: 0.7533, Val Loss: 1.2400, Val Accuracy: 0.6786
Epoch 5078/10000, Train Loss: 1.1593, Train Accuracy: 0.7489, Val Loss: 1.2400, Val Accuracy: 0.6786
Epoch 5079/10000, Train Loss: 1.1528, Train Accuracy: 0.7679, Val Loss: 1.2399, Val Accuracy: 0.6786
Epoch 5080/10000, Train Loss: 1.1571, Train Accuracy: 0.7656, Val Loss: 1.2401, Val Accuracy: 0.6786
Epoch 5081/10000, Train Loss: 1.1554, Train Accuracy: 0.7600, Val Loss: 1.2400, Val Accuracy: 0.6786
Epoch 5082/10000, Train Loss: 1.1537, Train Accuracy: 0.7556, Val Loss: 1.2400, Val Accuracy: 0.6786
Epoch 5083/10000, Train Loss: 1.1667, Train Accuracy: 0.7433, Val Loss: 1.2399, Val Accuracy: 0.6786
Epoch 5084/10000, Train Loss: 1.1601, Train Accuracy: 0.7545, Val Loss: 1.2398, Val Accuracy: 0.6741
Epoch 5085/10000, Train Loss: 1.1581, Train Accuracy: 0.7679, Val Loss: 1.2396, Val Accuracy: 0.6741
Epoch 5086/10000, Train Loss: 1.1598, Train Accuracy: 0.7478, Val Loss: 1.2397, Val Accuracy: 0.6741
Epoch 5087/10000, Train Loss: 1.1688, Train Accuracy: 0.7556, Val Loss: 1.2396, Val Accuracy: 0.6786
Epoch 5088/10000, Train Loss: 1.1581, Train Accuracy: 0.7600, Val Loss: 1.2396, Val Accuracy: 0.6786
Epoch 5089/10000, Train Loss: 1.1523, Train Accuracy: 0.7690, Val Loss: 1.2397, Val Accuracy: 0.6786
Epoch 5090/10000, Train Loss: 1.1583, Train Accuracy: 0.7623, Val Loss: 1.2396, Val Accuracy: 0.6786
Epoch 5091/10000, Train Loss: 1.1581, Train Accuracy: 0.7545, Val Loss: 1.2398, Val Accuracy: 0.6786
Epoch 5092/10000, Train Loss: 1.1580, Train Accuracy: 0.7679, Val Loss: 1.2394, Val Accuracy: 0.6786
Epoch 5093/10000, Train Loss: 1.1599, Train Accuracy: 0.7578, Val Loss: 1.2394, Val Accuracy: 0.6786
Epoch 5094/10000, Train Loss: 1.1618, Train Accuracy: 0.7500, Val Loss: 1.2393, Val Accuracy: 0.6786
Epoch 5095/10000, Train Loss: 1.1632, Train Accuracy: 0.7478, Val Loss: 1.2390, Val Accuracy: 0.6786
Epoch 5096/10000, Train Loss: 1.1690, Train Accuracy: 0.7433, Val Loss: 1.2391, Val Accuracy: 0.6786
Epoch 5097/10000, Train Loss: 1.1499, Train Accuracy: 0.7701, Val Loss: 1.2392, Val Accuracy: 0.6741
Epoch 5098/10000, Train Loss: 1.1532, Train Accuracy: 0.7589, Val Loss: 1.2390, Val Accuracy: 0.6741
Epoch 5099/10000, Train Loss: 1.1596, Train Accuracy: 0.7589, Val Loss: 1.2389, Val Accuracy: 0.6741
Epoch 5100/10000, Train Loss: 1.1485, Train Accuracy: 0.7690, Val Loss: 1.2390, Val Accuracy: 0.6741
Epoch 5101/10000, Train Loss: 1.1610, Train Accuracy: 0.7545, Val Loss: 1.2388, Val Accuracy: 0.6786
Epoch 5102/10000, Train Loss: 1.1564, Train Accuracy: 0.7545, Val Loss: 1.2388, Val Accuracy: 0.6786
Epoch 5103/10000, Train Loss: 1.1467, Train Accuracy: 0.7779, Val Loss: 1.2387, Val Accuracy: 0.6786
Epoch 5104/10000, Train Loss: 1.1621, Train Accuracy: 0.7600, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5105/10000, Train Loss: 1.1539, Train Accuracy: 0.7634, Val Loss: 1.2387, Val Accuracy: 0.6741
Epoch 5106/10000, Train Loss: 1.1683, Train Accuracy: 0.7467, Val Loss: 1.2388, Val Accuracy: 0.6741
Epoch 5107/10000, Train Loss: 1.1641, Train Accuracy: 0.7500, Val Loss: 1.2387, Val Accuracy: 0.6741
Epoch 5108/10000, Train Loss: 1.1602, Train Accuracy: 0.7600, Val Loss: 1.2387, Val Accuracy: 0.6741
Epoch 5109/10000, Train Loss: 1.1470, Train Accuracy: 0.7667, Val Loss: 1.2386, Val Accuracy: 0.6741
Epoch 5110/10000, Train Loss: 1.1614, Train Accuracy: 0.7623, Val Loss: 1.2387, Val Accuracy: 0.6786
Epoch 5111/10000, Train Loss: 1.1644, Train Accuracy: 0.7455, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5112/10000, Train Loss: 1.1642, Train Accuracy: 0.7478, Val Loss: 1.2385, Val Accuracy: 0.6786
Epoch 5113/10000, Train Loss: 1.1484, Train Accuracy: 0.7779, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5114/10000, Train Loss: 1.1524, Train Accuracy: 0.7623, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5115/10000, Train Loss: 1.1629, Train Accuracy: 0.7600, Val Loss: 1.2385, Val Accuracy: 0.6786
Epoch 5116/10000, Train Loss: 1.1435, Train Accuracy: 0.7701, Val Loss: 1.2387, Val Accuracy: 0.6786
Epoch 5117/10000, Train Loss: 1.1650, Train Accuracy: 0.7612, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5118/10000, Train Loss: 1.1544, Train Accuracy: 0.7667, Val Loss: 1.2386, Val Accuracy: 0.6786
Epoch 5119/10000, Train Loss: 1.1611, Train Accuracy: 0.7634, Val Loss: 1.2388, Val Accuracy: 0.6786
Epoch 5120/10000, Train Loss: 1.1534, Train Accuracy: 0.7656, Val Loss: 1.2385, Val Accuracy: 0.6830
Epoch 5121/10000, Train Loss: 1.1617, Train Accuracy: 0.7533, Val Loss: 1.2384, Val Accuracy: 0.6830
Epoch 5122/10000, Train Loss: 1.1578, Train Accuracy: 0.7533, Val Loss: 1.2383, Val Accuracy: 0.6786
Epoch 5123/10000, Train Loss: 1.1570, Train Accuracy: 0.7545, Val Loss: 1.2382, Val Accuracy: 0.6830
Epoch 5124/10000, Train Loss: 1.1566, Train Accuracy: 0.7679, Val Loss: 1.2381, Val Accuracy: 0.6830
Epoch 5125/10000, Train Loss: 1.1569, Train Accuracy: 0.7533, Val Loss: 1.2380, Val Accuracy: 0.6786
Epoch 5126/10000, Train Loss: 1.1555, Train Accuracy: 0.7556, Val Loss: 1.2379, Val Accuracy: 0.6830
Epoch 5127/10000, Train Loss: 1.1608, Train Accuracy: 0.7489, Val Loss: 1.2380, Val Accuracy: 0.6830
Epoch 5128/10000, Train Loss: 1.1611, Train Accuracy: 0.7511, Val Loss: 1.2380, Val Accuracy: 0.6830
Epoch 5129/10000, Train Loss: 1.1615, Train Accuracy: 0.7556, Val Loss: 1.2382, Val Accuracy: 0.6786
Epoch 5130/10000, Train Loss: 1.1598, Train Accuracy: 0.7612, Val Loss: 1.2381, Val Accuracy: 0.6786
Epoch 5131/10000, Train Loss: 1.1492, Train Accuracy: 0.7656, Val Loss: 1.2380, Val Accuracy: 0.6741
Epoch 5132/10000, Train Loss: 1.1494, Train Accuracy: 0.7634, Val Loss: 1.2381, Val Accuracy: 0.6741
Epoch 5133/10000, Train Loss: 1.1589, Train Accuracy: 0.7600, Val Loss: 1.2381, Val Accuracy: 0.6696
Epoch 5134/10000, Train Loss: 1.1538, Train Accuracy: 0.7634, Val Loss: 1.2382, Val Accuracy: 0.6696
Epoch 5135/10000, Train Loss: 1.1578, Train Accuracy: 0.7589, Val Loss: 1.2382, Val Accuracy: 0.6696
Epoch 5136/10000, Train Loss: 1.1544, Train Accuracy: 0.7623, Val Loss: 1.2380, Val Accuracy: 0.6696
Epoch 5137/10000, Train Loss: 1.1531, Train Accuracy: 0.7667, Val Loss: 1.2379, Val Accuracy: 0.6741
Epoch 5138/10000, Train Loss: 1.1584, Train Accuracy: 0.7623, Val Loss: 1.2378, Val Accuracy: 0.6741
Epoch 5139/10000, Train Loss: 1.1596, Train Accuracy: 0.7500, Val Loss: 1.2379, Val Accuracy: 0.6741
Epoch 5140/10000, Train Loss: 1.1598, Train Accuracy: 0.7578, Val Loss: 1.2378, Val Accuracy: 0.6786
Epoch 5141/10000, Train Loss: 1.1640, Train Accuracy: 0.7545, Val Loss: 1.2378, Val Accuracy: 0.6741
Epoch 5142/10000, Train Loss: 1.1522, Train Accuracy: 0.7746, Val Loss: 1.2378, Val Accuracy: 0.6786
Epoch 5143/10000, Train Loss: 1.1569, Train Accuracy: 0.7667, Val Loss: 1.2376, Val Accuracy: 0.6786
Epoch 5144/10000, Train Loss: 1.1560, Train Accuracy: 0.7545, Val Loss: 1.2376, Val Accuracy: 0.6786
Epoch 5145/10000, Train Loss: 1.1601, Train Accuracy: 0.7556, Val Loss: 1.2374, Val Accuracy: 0.6830
Epoch 5146/10000, Train Loss: 1.1629, Train Accuracy: 0.7522, Val Loss: 1.2372, Val Accuracy: 0.6830
Epoch 5147/10000, Train Loss: 1.1543, Train Accuracy: 0.7612, Val Loss: 1.2370, Val Accuracy: 0.6786
Epoch 5148/10000, Train Loss: 1.1681, Train Accuracy: 0.7388, Val Loss: 1.2373, Val Accuracy: 0.6741
Epoch 5149/10000, Train Loss: 1.1565, Train Accuracy: 0.7600, Val Loss: 1.2373, Val Accuracy: 0.6786
Epoch 5150/10000, Train Loss: 1.1666, Train Accuracy: 0.7444, Val Loss: 1.2372, Val Accuracy: 0.6830
Epoch 5151/10000, Train Loss: 1.1587, Train Accuracy: 0.7656, Val Loss: 1.2370, Val Accuracy: 0.6830
Epoch 5152/10000, Train Loss: 1.1610, Train Accuracy: 0.7500, Val Loss: 1.2372, Val Accuracy: 0.6830
Epoch 5153/10000, Train Loss: 1.1588, Train Accuracy: 0.7556, Val Loss: 1.2374, Val Accuracy: 0.6830
Epoch 5154/10000, Train Loss: 1.1589, Train Accuracy: 0.7545, Val Loss: 1.2374, Val Accuracy: 0.6830
Epoch 5155/10000, Train Loss: 1.1648, Train Accuracy: 0.7522, Val Loss: 1.2373, Val Accuracy: 0.6830
Epoch 5156/10000, Train Loss: 1.1638, Train Accuracy: 0.7489, Val Loss: 1.2372, Val Accuracy: 0.6741
Epoch 5157/10000, Train Loss: 1.1575, Train Accuracy: 0.7467, Val Loss: 1.2373, Val Accuracy: 0.6830
Epoch 5158/10000, Train Loss: 1.1663, Train Accuracy: 0.7455, Val Loss: 1.2373, Val Accuracy: 0.6830
Epoch 5159/10000, Train Loss: 1.1529, Train Accuracy: 0.7623, Val Loss: 1.2370, Val Accuracy: 0.6830
Epoch 5160/10000, Train Loss: 1.1655, Train Accuracy: 0.7444, Val Loss: 1.2370, Val Accuracy: 0.6875
Epoch 5161/10000, Train Loss: 1.1673, Train Accuracy: 0.7433, Val Loss: 1.2370, Val Accuracy: 0.6830
Epoch 5162/10000, Train Loss: 1.1650, Train Accuracy: 0.7511, Val Loss: 1.2369, Val Accuracy: 0.6830
Epoch 5163/10000, Train Loss: 1.1474, Train Accuracy: 0.7757, Val Loss: 1.2370, Val Accuracy: 0.6830
Epoch 5164/10000, Train Loss: 1.1657, Train Accuracy: 0.7556, Val Loss: 1.2368, Val Accuracy: 0.6830
Epoch 5165/10000, Train Loss: 1.1599, Train Accuracy: 0.7589, Val Loss: 1.2368, Val Accuracy: 0.6830
Epoch 5166/10000, Train Loss: 1.1509, Train Accuracy: 0.7656, Val Loss: 1.2364, Val Accuracy: 0.6830
Epoch 5167/10000, Train Loss: 1.1626, Train Accuracy: 0.7545, Val Loss: 1.2365, Val Accuracy: 0.6830
Epoch 5168/10000, Train Loss: 1.1489, Train Accuracy: 0.7589, Val Loss: 1.2365, Val Accuracy: 0.6830
Epoch 5169/10000, Train Loss: 1.1505, Train Accuracy: 0.7712, Val Loss: 1.2365, Val Accuracy: 0.6830
Epoch 5170/10000, Train Loss: 1.1589, Train Accuracy: 0.7600, Val Loss: 1.2366, Val Accuracy: 0.6830
Epoch 5171/10000, Train Loss: 1.1546, Train Accuracy: 0.7600, Val Loss: 1.2367, Val Accuracy: 0.6830
Epoch 5172/10000, Train Loss: 1.1626, Train Accuracy: 0.7500, Val Loss: 1.2367, Val Accuracy: 0.6830
Epoch 5173/10000, Train Loss: 1.1591, Train Accuracy: 0.7578, Val Loss: 1.2366, Val Accuracy: 0.6875
Epoch 5174/10000, Train Loss: 1.1553, Train Accuracy: 0.7589, Val Loss: 1.2365, Val Accuracy: 0.6830
Epoch 5175/10000, Train Loss: 1.1611, Train Accuracy: 0.7511, Val Loss: 1.2366, Val Accuracy: 0.6830
Epoch 5176/10000, Train Loss: 1.1768, Train Accuracy: 0.7333, Val Loss: 1.2367, Val Accuracy: 0.6830
Epoch 5177/10000, Train Loss: 1.1635, Train Accuracy: 0.7567, Val Loss: 1.2365, Val Accuracy: 0.6830
Epoch 5178/10000, Train Loss: 1.1483, Train Accuracy: 0.7667, Val Loss: 1.2362, Val Accuracy: 0.6830
Epoch 5179/10000, Train Loss: 1.1551, Train Accuracy: 0.7623, Val Loss: 1.2362, Val Accuracy: 0.6830
Epoch 5180/10000, Train Loss: 1.1420, Train Accuracy: 0.7768, Val Loss: 1.2363, Val Accuracy: 0.6830
Epoch 5181/10000, Train Loss: 1.1517, Train Accuracy: 0.7634, Val Loss: 1.2362, Val Accuracy: 0.6830
Epoch 5182/10000, Train Loss: 1.1573, Train Accuracy: 0.7589, Val Loss: 1.2361, Val Accuracy: 0.6830
Epoch 5183/10000, Train Loss: 1.1532, Train Accuracy: 0.7645, Val Loss: 1.2362, Val Accuracy: 0.6830
Epoch 5184/10000, Train Loss: 1.1436, Train Accuracy: 0.7679, Val Loss: 1.2361, Val Accuracy: 0.6830
Epoch 5185/10000, Train Loss: 1.1628, Train Accuracy: 0.7522, Val Loss: 1.2360, Val Accuracy: 0.6830
Epoch 5186/10000, Train Loss: 1.1566, Train Accuracy: 0.7545, Val Loss: 1.2360, Val Accuracy: 0.6830
Epoch 5187/10000, Train Loss: 1.1598, Train Accuracy: 0.7600, Val Loss: 1.2361, Val Accuracy: 0.6830
Epoch 5188/10000, Train Loss: 1.1492, Train Accuracy: 0.7589, Val Loss: 1.2360, Val Accuracy: 0.6830
Epoch 5189/10000, Train Loss: 1.1531, Train Accuracy: 0.7578, Val Loss: 1.2360, Val Accuracy: 0.6830
Epoch 5190/10000, Train Loss: 1.1540, Train Accuracy: 0.7567, Val Loss: 1.2358, Val Accuracy: 0.6830
Epoch 5191/10000, Train Loss: 1.1711, Train Accuracy: 0.7377, Val Loss: 1.2357, Val Accuracy: 0.6786
Epoch 5192/10000, Train Loss: 1.1613, Train Accuracy: 0.7623, Val Loss: 1.2357, Val Accuracy: 0.6786
Epoch 5193/10000, Train Loss: 1.1453, Train Accuracy: 0.7779, Val Loss: 1.2355, Val Accuracy: 0.6786
Epoch 5194/10000, Train Loss: 1.1539, Train Accuracy: 0.7645, Val Loss: 1.2354, Val Accuracy: 0.6786
Epoch 5195/10000, Train Loss: 1.1468, Train Accuracy: 0.7779, Val Loss: 1.2352, Val Accuracy: 0.6786
Epoch 5196/10000, Train Loss: 1.1536, Train Accuracy: 0.7667, Val Loss: 1.2354, Val Accuracy: 0.6741
Epoch 5197/10000, Train Loss: 1.1521, Train Accuracy: 0.7701, Val Loss: 1.2354, Val Accuracy: 0.6741
Epoch 5198/10000, Train Loss: 1.1615, Train Accuracy: 0.7500, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5199/10000, Train Loss: 1.1540, Train Accuracy: 0.7667, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5200/10000, Train Loss: 1.1641, Train Accuracy: 0.7578, Val Loss: 1.2354, Val Accuracy: 0.6786
Epoch 5201/10000, Train Loss: 1.1611, Train Accuracy: 0.7589, Val Loss: 1.2353, Val Accuracy: 0.6830
Epoch 5202/10000, Train Loss: 1.1530, Train Accuracy: 0.7634, Val Loss: 1.2352, Val Accuracy: 0.6786
Epoch 5203/10000, Train Loss: 1.1559, Train Accuracy: 0.7511, Val Loss: 1.2353, Val Accuracy: 0.6830
Epoch 5204/10000, Train Loss: 1.1432, Train Accuracy: 0.7746, Val Loss: 1.2353, Val Accuracy: 0.6741
Epoch 5205/10000, Train Loss: 1.1660, Train Accuracy: 0.7467, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5206/10000, Train Loss: 1.1643, Train Accuracy: 0.7489, Val Loss: 1.2354, Val Accuracy: 0.6786
Epoch 5207/10000, Train Loss: 1.1493, Train Accuracy: 0.7712, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5208/10000, Train Loss: 1.1673, Train Accuracy: 0.7366, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5209/10000, Train Loss: 1.1510, Train Accuracy: 0.7589, Val Loss: 1.2353, Val Accuracy: 0.6786
Epoch 5210/10000, Train Loss: 1.1507, Train Accuracy: 0.7533, Val Loss: 1.2351, Val Accuracy: 0.6830
Epoch 5211/10000, Train Loss: 1.1566, Train Accuracy: 0.7612, Val Loss: 1.2351, Val Accuracy: 0.6875
Epoch 5212/10000, Train Loss: 1.1565, Train Accuracy: 0.7600, Val Loss: 1.2351, Val Accuracy: 0.6830
Epoch 5213/10000, Train Loss: 1.1487, Train Accuracy: 0.7746, Val Loss: 1.2350, Val Accuracy: 0.6830
Epoch 5214/10000, Train Loss: 1.1546, Train Accuracy: 0.7634, Val Loss: 1.2351, Val Accuracy: 0.6875
Epoch 5215/10000, Train Loss: 1.1508, Train Accuracy: 0.7690, Val Loss: 1.2347, Val Accuracy: 0.6875
Epoch 5216/10000, Train Loss: 1.1655, Train Accuracy: 0.7533, Val Loss: 1.2348, Val Accuracy: 0.6830
Epoch 5217/10000, Train Loss: 1.1412, Train Accuracy: 0.7779, Val Loss: 1.2347, Val Accuracy: 0.6830
Epoch 5218/10000, Train Loss: 1.1505, Train Accuracy: 0.7623, Val Loss: 1.2346, Val Accuracy: 0.6875
Epoch 5219/10000, Train Loss: 1.1486, Train Accuracy: 0.7623, Val Loss: 1.2344, Val Accuracy: 0.6875
Epoch 5220/10000, Train Loss: 1.1524, Train Accuracy: 0.7645, Val Loss: 1.2345, Val Accuracy: 0.6920
Epoch 5221/10000, Train Loss: 1.1620, Train Accuracy: 0.7489, Val Loss: 1.2343, Val Accuracy: 0.6875
Epoch 5222/10000, Train Loss: 1.1562, Train Accuracy: 0.7701, Val Loss: 1.2341, Val Accuracy: 0.6920
Epoch 5223/10000, Train Loss: 1.1553, Train Accuracy: 0.7545, Val Loss: 1.2341, Val Accuracy: 0.6875
Epoch 5224/10000, Train Loss: 1.1507, Train Accuracy: 0.7656, Val Loss: 1.2340, Val Accuracy: 0.6875
Epoch 5225/10000, Train Loss: 1.1565, Train Accuracy: 0.7467, Val Loss: 1.2338, Val Accuracy: 0.6875
Epoch 5226/10000, Train Loss: 1.1464, Train Accuracy: 0.7690, Val Loss: 1.2338, Val Accuracy: 0.6875
Epoch 5227/10000, Train Loss: 1.1534, Train Accuracy: 0.7645, Val Loss: 1.2336, Val Accuracy: 0.6875
Epoch 5228/10000, Train Loss: 1.1454, Train Accuracy: 0.7779, Val Loss: 1.2333, Val Accuracy: 0.6875
Epoch 5229/10000, Train Loss: 1.1630, Train Accuracy: 0.7422, Val Loss: 1.2333, Val Accuracy: 0.6875
Epoch 5230/10000, Train Loss: 1.1600, Train Accuracy: 0.7578, Val Loss: 1.2335, Val Accuracy: 0.6875
Epoch 5231/10000, Train Loss: 1.1550, Train Accuracy: 0.7645, Val Loss: 1.2336, Val Accuracy: 0.6875
Epoch 5232/10000, Train Loss: 1.1657, Train Accuracy: 0.7500, Val Loss: 1.2338, Val Accuracy: 0.6875
Epoch 5233/10000, Train Loss: 1.1551, Train Accuracy: 0.7567, Val Loss: 1.2337, Val Accuracy: 0.6875
Epoch 5234/10000, Train Loss: 1.1526, Train Accuracy: 0.7679, Val Loss: 1.2336, Val Accuracy: 0.6830
Epoch 5235/10000, Train Loss: 1.1536, Train Accuracy: 0.7690, Val Loss: 1.2334, Val Accuracy: 0.6875
Epoch 5236/10000, Train Loss: 1.1624, Train Accuracy: 0.7500, Val Loss: 1.2332, Val Accuracy: 0.6830
Epoch 5237/10000, Train Loss: 1.1513, Train Accuracy: 0.7589, Val Loss: 1.2331, Val Accuracy: 0.6830
Epoch 5238/10000, Train Loss: 1.1552, Train Accuracy: 0.7679, Val Loss: 1.2333, Val Accuracy: 0.6830
Epoch 5239/10000, Train Loss: 1.1506, Train Accuracy: 0.7656, Val Loss: 1.2331, Val Accuracy: 0.6830
Epoch 5240/10000, Train Loss: 1.1522, Train Accuracy: 0.7679, Val Loss: 1.2333, Val Accuracy: 0.6830
Epoch 5241/10000, Train Loss: 1.1437, Train Accuracy: 0.7746, Val Loss: 1.2331, Val Accuracy: 0.6830
Epoch 5242/10000, Train Loss: 1.1650, Train Accuracy: 0.7511, Val Loss: 1.2330, Val Accuracy: 0.6830
Epoch 5243/10000, Train Loss: 1.1549, Train Accuracy: 0.7679, Val Loss: 1.2329, Val Accuracy: 0.6830
Epoch 5244/10000, Train Loss: 1.1521, Train Accuracy: 0.7768, Val Loss: 1.2329, Val Accuracy: 0.6875
Epoch 5245/10000, Train Loss: 1.1467, Train Accuracy: 0.7812, Val Loss: 1.2328, Val Accuracy: 0.6830
Epoch 5246/10000, Train Loss: 1.1463, Train Accuracy: 0.7679, Val Loss: 1.2329, Val Accuracy: 0.6830
Epoch 5247/10000, Train Loss: 1.1608, Train Accuracy: 0.7567, Val Loss: 1.2328, Val Accuracy: 0.6830
Epoch 5248/10000, Train Loss: 1.1492, Train Accuracy: 0.7556, Val Loss: 1.2329, Val Accuracy: 0.6830
Epoch 5249/10000, Train Loss: 1.1408, Train Accuracy: 0.7768, Val Loss: 1.2331, Val Accuracy: 0.6830
Epoch 5250/10000, Train Loss: 1.1423, Train Accuracy: 0.7734, Val Loss: 1.2330, Val Accuracy: 0.6830
Epoch 5251/10000, Train Loss: 1.1495, Train Accuracy: 0.7656, Val Loss: 1.2328, Val Accuracy: 0.6830
Epoch 5252/10000, Train Loss: 1.1521, Train Accuracy: 0.7612, Val Loss: 1.2329, Val Accuracy: 0.6830
Epoch 5253/10000, Train Loss: 1.1553, Train Accuracy: 0.7589, Val Loss: 1.2325, Val Accuracy: 0.6830
Epoch 5254/10000, Train Loss: 1.1462, Train Accuracy: 0.7746, Val Loss: 1.2324, Val Accuracy: 0.6786
Epoch 5255/10000, Train Loss: 1.1398, Train Accuracy: 0.7757, Val Loss: 1.2324, Val Accuracy: 0.6786
Epoch 5256/10000, Train Loss: 1.1519, Train Accuracy: 0.7690, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5257/10000, Train Loss: 1.1529, Train Accuracy: 0.7712, Val Loss: 1.2324, Val Accuracy: 0.6830
Epoch 5258/10000, Train Loss: 1.1429, Train Accuracy: 0.7667, Val Loss: 1.2324, Val Accuracy: 0.6830
Epoch 5259/10000, Train Loss: 1.1507, Train Accuracy: 0.7667, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5260/10000, Train Loss: 1.1621, Train Accuracy: 0.7511, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5261/10000, Train Loss: 1.1606, Train Accuracy: 0.7556, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5262/10000, Train Loss: 1.1410, Train Accuracy: 0.7667, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5263/10000, Train Loss: 1.1509, Train Accuracy: 0.7589, Val Loss: 1.2324, Val Accuracy: 0.6830
Epoch 5264/10000, Train Loss: 1.1483, Train Accuracy: 0.7701, Val Loss: 1.2322, Val Accuracy: 0.6786
Epoch 5265/10000, Train Loss: 1.1538, Train Accuracy: 0.7567, Val Loss: 1.2324, Val Accuracy: 0.6786
Epoch 5266/10000, Train Loss: 1.1541, Train Accuracy: 0.7645, Val Loss: 1.2323, Val Accuracy: 0.6786
Epoch 5267/10000, Train Loss: 1.1558, Train Accuracy: 0.7690, Val Loss: 1.2322, Val Accuracy: 0.6830
Epoch 5268/10000, Train Loss: 1.1465, Train Accuracy: 0.7746, Val Loss: 1.2322, Val Accuracy: 0.6830
Epoch 5269/10000, Train Loss: 1.1417, Train Accuracy: 0.7690, Val Loss: 1.2322, Val Accuracy: 0.6830
Epoch 5270/10000, Train Loss: 1.1550, Train Accuracy: 0.7500, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5271/10000, Train Loss: 1.1415, Train Accuracy: 0.7734, Val Loss: 1.2323, Val Accuracy: 0.6830
Epoch 5272/10000, Train Loss: 1.1535, Train Accuracy: 0.7600, Val Loss: 1.2321, Val Accuracy: 0.6830
Epoch 5273/10000, Train Loss: 1.1458, Train Accuracy: 0.7690, Val Loss: 1.2318, Val Accuracy: 0.6830
Epoch 5274/10000, Train Loss: 1.1455, Train Accuracy: 0.7645, Val Loss: 1.2317, Val Accuracy: 0.6830
Epoch 5275/10000, Train Loss: 1.1420, Train Accuracy: 0.7857, Val Loss: 1.2314, Val Accuracy: 0.6830
Epoch 5276/10000, Train Loss: 1.1515, Train Accuracy: 0.7634, Val Loss: 1.2314, Val Accuracy: 0.6830
Epoch 5277/10000, Train Loss: 1.1569, Train Accuracy: 0.7612, Val Loss: 1.2317, Val Accuracy: 0.6830
Epoch 5278/10000, Train Loss: 1.1429, Train Accuracy: 0.7679, Val Loss: 1.2316, Val Accuracy: 0.6830
Epoch 5279/10000, Train Loss: 1.1467, Train Accuracy: 0.7757, Val Loss: 1.2314, Val Accuracy: 0.6830
Epoch 5280/10000, Train Loss: 1.1453, Train Accuracy: 0.7701, Val Loss: 1.2313, Val Accuracy: 0.6830
Epoch 5281/10000, Train Loss: 1.1567, Train Accuracy: 0.7667, Val Loss: 1.2314, Val Accuracy: 0.6830
Epoch 5282/10000, Train Loss: 1.1408, Train Accuracy: 0.7835, Val Loss: 1.2313, Val Accuracy: 0.6830
Epoch 5283/10000, Train Loss: 1.1526, Train Accuracy: 0.7634, Val Loss: 1.2313, Val Accuracy: 0.6830
Epoch 5284/10000, Train Loss: 1.1471, Train Accuracy: 0.7790, Val Loss: 1.2314, Val Accuracy: 0.6786
Epoch 5285/10000, Train Loss: 1.1653, Train Accuracy: 0.7489, Val Loss: 1.2314, Val Accuracy: 0.6830
Epoch 5286/10000, Train Loss: 1.1419, Train Accuracy: 0.7812, Val Loss: 1.2315, Val Accuracy: 0.6830
Epoch 5287/10000, Train Loss: 1.1408, Train Accuracy: 0.7746, Val Loss: 1.2317, Val Accuracy: 0.6786
Epoch 5288/10000, Train Loss: 1.1503, Train Accuracy: 0.7645, Val Loss: 1.2318, Val Accuracy: 0.6786
Epoch 5289/10000, Train Loss: 1.1467, Train Accuracy: 0.7612, Val Loss: 1.2319, Val Accuracy: 0.6786
Epoch 5290/10000, Train Loss: 1.1450, Train Accuracy: 0.7701, Val Loss: 1.2316, Val Accuracy: 0.6786
Epoch 5291/10000, Train Loss: 1.1496, Train Accuracy: 0.7723, Val Loss: 1.2315, Val Accuracy: 0.6786
Epoch 5292/10000, Train Loss: 1.1626, Train Accuracy: 0.7533, Val Loss: 1.2316, Val Accuracy: 0.6830
Epoch 5293/10000, Train Loss: 1.1433, Train Accuracy: 0.7734, Val Loss: 1.2313, Val Accuracy: 0.6830
Epoch 5294/10000, Train Loss: 1.1467, Train Accuracy: 0.7679, Val Loss: 1.2313, Val Accuracy: 0.6830
Epoch 5295/10000, Train Loss: 1.1585, Train Accuracy: 0.7545, Val Loss: 1.2312, Val Accuracy: 0.6830
Epoch 5296/10000, Train Loss: 1.1417, Train Accuracy: 0.7757, Val Loss: 1.2310, Val Accuracy: 0.6830
Epoch 5297/10000, Train Loss: 1.1509, Train Accuracy: 0.7679, Val Loss: 1.2309, Val Accuracy: 0.6875
Epoch 5298/10000, Train Loss: 1.1474, Train Accuracy: 0.7623, Val Loss: 1.2308, Val Accuracy: 0.6830
Epoch 5299/10000, Train Loss: 1.1506, Train Accuracy: 0.7679, Val Loss: 1.2306, Val Accuracy: 0.6875
Epoch 5300/10000, Train Loss: 1.1393, Train Accuracy: 0.7790, Val Loss: 1.2305, Val Accuracy: 0.6875
Epoch 5301/10000, Train Loss: 1.1627, Train Accuracy: 0.7478, Val Loss: 1.2304, Val Accuracy: 0.6875
Epoch 5302/10000, Train Loss: 1.1508, Train Accuracy: 0.7746, Val Loss: 1.2302, Val Accuracy: 0.6875
Epoch 5303/10000, Train Loss: 1.1412, Train Accuracy: 0.7801, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5304/10000, Train Loss: 1.1529, Train Accuracy: 0.7667, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5305/10000, Train Loss: 1.1412, Train Accuracy: 0.7790, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5306/10000, Train Loss: 1.1393, Train Accuracy: 0.7768, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5307/10000, Train Loss: 1.1395, Train Accuracy: 0.7779, Val Loss: 1.2298, Val Accuracy: 0.6875
Epoch 5308/10000, Train Loss: 1.1452, Train Accuracy: 0.7734, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5309/10000, Train Loss: 1.1435, Train Accuracy: 0.7757, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5310/10000, Train Loss: 1.1498, Train Accuracy: 0.7701, Val Loss: 1.2299, Val Accuracy: 0.6875
Epoch 5311/10000, Train Loss: 1.1468, Train Accuracy: 0.7801, Val Loss: 1.2301, Val Accuracy: 0.6830
Epoch 5312/10000, Train Loss: 1.1402, Train Accuracy: 0.7824, Val Loss: 1.2303, Val Accuracy: 0.6830
Epoch 5313/10000, Train Loss: 1.1551, Train Accuracy: 0.7656, Val Loss: 1.2304, Val Accuracy: 0.6830
Epoch 5314/10000, Train Loss: 1.1501, Train Accuracy: 0.7623, Val Loss: 1.2303, Val Accuracy: 0.6830
Epoch 5315/10000, Train Loss: 1.1341, Train Accuracy: 0.7846, Val Loss: 1.2302, Val Accuracy: 0.6830
Epoch 5316/10000, Train Loss: 1.1557, Train Accuracy: 0.7600, Val Loss: 1.2302, Val Accuracy: 0.6830
Epoch 5317/10000, Train Loss: 1.1486, Train Accuracy: 0.7679, Val Loss: 1.2299, Val Accuracy: 0.6830
Epoch 5318/10000, Train Loss: 1.1564, Train Accuracy: 0.7533, Val Loss: 1.2301, Val Accuracy: 0.6830
Epoch 5319/10000, Train Loss: 1.1480, Train Accuracy: 0.7645, Val Loss: 1.2298, Val Accuracy: 0.6830
Epoch 5320/10000, Train Loss: 1.1498, Train Accuracy: 0.7645, Val Loss: 1.2296, Val Accuracy: 0.6830
Epoch 5321/10000, Train Loss: 1.1554, Train Accuracy: 0.7567, Val Loss: 1.2294, Val Accuracy: 0.6875
Epoch 5322/10000, Train Loss: 1.1414, Train Accuracy: 0.7768, Val Loss: 1.2294, Val Accuracy: 0.6875
Epoch 5323/10000, Train Loss: 1.1388, Train Accuracy: 0.7734, Val Loss: 1.2293, Val Accuracy: 0.6875
Epoch 5324/10000, Train Loss: 1.1393, Train Accuracy: 0.7801, Val Loss: 1.2292, Val Accuracy: 0.6875
Epoch 5325/10000, Train Loss: 1.1450, Train Accuracy: 0.7667, Val Loss: 1.2293, Val Accuracy: 0.6830
Epoch 5326/10000, Train Loss: 1.1452, Train Accuracy: 0.7757, Val Loss: 1.2293, Val Accuracy: 0.6830
Epoch 5327/10000, Train Loss: 1.1474, Train Accuracy: 0.7623, Val Loss: 1.2294, Val Accuracy: 0.6786
Epoch 5328/10000, Train Loss: 1.1517, Train Accuracy: 0.7612, Val Loss: 1.2294, Val Accuracy: 0.6830
Epoch 5329/10000, Train Loss: 1.1459, Train Accuracy: 0.7701, Val Loss: 1.2294, Val Accuracy: 0.6786
Epoch 5330/10000, Train Loss: 1.1452, Train Accuracy: 0.7679, Val Loss: 1.2293, Val Accuracy: 0.6786
Epoch 5331/10000, Train Loss: 1.1513, Train Accuracy: 0.7522, Val Loss: 1.2294, Val Accuracy: 0.6786
Epoch 5332/10000, Train Loss: 1.1557, Train Accuracy: 0.7645, Val Loss: 1.2293, Val Accuracy: 0.6786
Epoch 5333/10000, Train Loss: 1.1495, Train Accuracy: 0.7634, Val Loss: 1.2291, Val Accuracy: 0.6786
Epoch 5334/10000, Train Loss: 1.1557, Train Accuracy: 0.7533, Val Loss: 1.2290, Val Accuracy: 0.6786
Epoch 5335/10000, Train Loss: 1.1430, Train Accuracy: 0.7779, Val Loss: 1.2289, Val Accuracy: 0.6786
Epoch 5336/10000, Train Loss: 1.1474, Train Accuracy: 0.7679, Val Loss: 1.2289, Val Accuracy: 0.6786
Epoch 5337/10000, Train Loss: 1.1519, Train Accuracy: 0.7712, Val Loss: 1.2287, Val Accuracy: 0.6786
Epoch 5338/10000, Train Loss: 1.1470, Train Accuracy: 0.7746, Val Loss: 1.2288, Val Accuracy: 0.6830
Epoch 5339/10000, Train Loss: 1.1436, Train Accuracy: 0.7768, Val Loss: 1.2286, Val Accuracy: 0.6830
Epoch 5340/10000, Train Loss: 1.1454, Train Accuracy: 0.7679, Val Loss: 1.2286, Val Accuracy: 0.6830
Epoch 5341/10000, Train Loss: 1.1578, Train Accuracy: 0.7545, Val Loss: 1.2285, Val Accuracy: 0.6830
Epoch 5342/10000, Train Loss: 1.1513, Train Accuracy: 0.7634, Val Loss: 1.2286, Val Accuracy: 0.6830
Epoch 5343/10000, Train Loss: 1.1436, Train Accuracy: 0.7723, Val Loss: 1.2286, Val Accuracy: 0.6830
Epoch 5344/10000, Train Loss: 1.1472, Train Accuracy: 0.7645, Val Loss: 1.2287, Val Accuracy: 0.6830
Epoch 5345/10000, Train Loss: 1.1486, Train Accuracy: 0.7779, Val Loss: 1.2289, Val Accuracy: 0.6786
Epoch 5346/10000, Train Loss: 1.1634, Train Accuracy: 0.7522, Val Loss: 1.2289, Val Accuracy: 0.6786
Epoch 5347/10000, Train Loss: 1.1427, Train Accuracy: 0.7746, Val Loss: 1.2288, Val Accuracy: 0.6786
Epoch 5348/10000, Train Loss: 1.1508, Train Accuracy: 0.7690, Val Loss: 1.2288, Val Accuracy: 0.6786
Epoch 5349/10000, Train Loss: 1.1522, Train Accuracy: 0.7589, Val Loss: 1.2288, Val Accuracy: 0.6786
Epoch 5350/10000, Train Loss: 1.1312, Train Accuracy: 0.7824, Val Loss: 1.2285, Val Accuracy: 0.6786
Epoch 5351/10000, Train Loss: 1.1401, Train Accuracy: 0.7768, Val Loss: 1.2285, Val Accuracy: 0.6786
Epoch 5352/10000, Train Loss: 1.1465, Train Accuracy: 0.7746, Val Loss: 1.2280, Val Accuracy: 0.6786
Epoch 5353/10000, Train Loss: 1.1430, Train Accuracy: 0.7734, Val Loss: 1.2280, Val Accuracy: 0.6786
Epoch 5354/10000, Train Loss: 1.1630, Train Accuracy: 0.7522, Val Loss: 1.2279, Val Accuracy: 0.6786
Epoch 5355/10000, Train Loss: 1.1554, Train Accuracy: 0.7567, Val Loss: 1.2281, Val Accuracy: 0.6830
Epoch 5356/10000, Train Loss: 1.1407, Train Accuracy: 0.7712, Val Loss: 1.2280, Val Accuracy: 0.6830
Epoch 5357/10000, Train Loss: 1.1501, Train Accuracy: 0.7623, Val Loss: 1.2280, Val Accuracy: 0.6830
Epoch 5358/10000, Train Loss: 1.1398, Train Accuracy: 0.7712, Val Loss: 1.2281, Val Accuracy: 0.6830
Epoch 5359/10000, Train Loss: 1.1535, Train Accuracy: 0.7634, Val Loss: 1.2279, Val Accuracy: 0.6830
Epoch 5360/10000, Train Loss: 1.1503, Train Accuracy: 0.7645, Val Loss: 1.2278, Val Accuracy: 0.6830
Epoch 5361/10000, Train Loss: 1.1476, Train Accuracy: 0.7578, Val Loss: 1.2276, Val Accuracy: 0.6830
Epoch 5362/10000, Train Loss: 1.1461, Train Accuracy: 0.7757, Val Loss: 1.2275, Val Accuracy: 0.6830
Epoch 5363/10000, Train Loss: 1.1507, Train Accuracy: 0.7701, Val Loss: 1.2277, Val Accuracy: 0.6830
Epoch 5364/10000, Train Loss: 1.1448, Train Accuracy: 0.7790, Val Loss: 1.2277, Val Accuracy: 0.6830
Epoch 5365/10000, Train Loss: 1.1440, Train Accuracy: 0.7701, Val Loss: 1.2277, Val Accuracy: 0.6830
Epoch 5366/10000, Train Loss: 1.1558, Train Accuracy: 0.7556, Val Loss: 1.2277, Val Accuracy: 0.6830
Epoch 5367/10000, Train Loss: 1.1329, Train Accuracy: 0.7857, Val Loss: 1.2277, Val Accuracy: 0.6830
Epoch 5368/10000, Train Loss: 1.1506, Train Accuracy: 0.7578, Val Loss: 1.2275, Val Accuracy: 0.6830
Epoch 5369/10000, Train Loss: 1.1466, Train Accuracy: 0.7723, Val Loss: 1.2277, Val Accuracy: 0.6786
Epoch 5370/10000, Train Loss: 1.1593, Train Accuracy: 0.7511, Val Loss: 1.2277, Val Accuracy: 0.6786
Epoch 5371/10000, Train Loss: 1.1400, Train Accuracy: 0.7790, Val Loss: 1.2276, Val Accuracy: 0.6786
Epoch 5372/10000, Train Loss: 1.1522, Train Accuracy: 0.7723, Val Loss: 1.2275, Val Accuracy: 0.6786
Epoch 5373/10000, Train Loss: 1.1471, Train Accuracy: 0.7757, Val Loss: 1.2275, Val Accuracy: 0.6786
Epoch 5374/10000, Train Loss: 1.1481, Train Accuracy: 0.7734, Val Loss: 1.2275, Val Accuracy: 0.6786
Epoch 5375/10000, Train Loss: 1.1425, Train Accuracy: 0.7746, Val Loss: 1.2274, Val Accuracy: 0.6786
Epoch 5376/10000, Train Loss: 1.1534, Train Accuracy: 0.7600, Val Loss: 1.2273, Val Accuracy: 0.6786
Epoch 5377/10000, Train Loss: 1.1523, Train Accuracy: 0.7634, Val Loss: 1.2273, Val Accuracy: 0.6786
Epoch 5378/10000, Train Loss: 1.1427, Train Accuracy: 0.7746, Val Loss: 1.2274, Val Accuracy: 0.6786
Epoch 5379/10000, Train Loss: 1.1531, Train Accuracy: 0.7667, Val Loss: 1.2275, Val Accuracy: 0.6786
Epoch 5380/10000, Train Loss: 1.1528, Train Accuracy: 0.7656, Val Loss: 1.2272, Val Accuracy: 0.6786
Epoch 5381/10000, Train Loss: 1.1377, Train Accuracy: 0.7757, Val Loss: 1.2271, Val Accuracy: 0.6786
Epoch 5382/10000, Train Loss: 1.1424, Train Accuracy: 0.7757, Val Loss: 1.2271, Val Accuracy: 0.6830
Epoch 5383/10000, Train Loss: 1.1342, Train Accuracy: 0.7790, Val Loss: 1.2269, Val Accuracy: 0.6830
Epoch 5384/10000, Train Loss: 1.1433, Train Accuracy: 0.7746, Val Loss: 1.2269, Val Accuracy: 0.6830
Epoch 5385/10000, Train Loss: 1.1449, Train Accuracy: 0.7790, Val Loss: 1.2270, Val Accuracy: 0.6830
Epoch 5386/10000, Train Loss: 1.1364, Train Accuracy: 0.7812, Val Loss: 1.2265, Val Accuracy: 0.6786
Epoch 5387/10000, Train Loss: 1.1407, Train Accuracy: 0.7757, Val Loss: 1.2264, Val Accuracy: 0.6830
Epoch 5388/10000, Train Loss: 1.1532, Train Accuracy: 0.7667, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5389/10000, Train Loss: 1.1459, Train Accuracy: 0.7757, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5390/10000, Train Loss: 1.1535, Train Accuracy: 0.7578, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5391/10000, Train Loss: 1.1584, Train Accuracy: 0.7567, Val Loss: 1.2263, Val Accuracy: 0.6875
Epoch 5392/10000, Train Loss: 1.1402, Train Accuracy: 0.7701, Val Loss: 1.2262, Val Accuracy: 0.6875
Epoch 5393/10000, Train Loss: 1.1517, Train Accuracy: 0.7589, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5394/10000, Train Loss: 1.1531, Train Accuracy: 0.7556, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5395/10000, Train Loss: 1.1481, Train Accuracy: 0.7645, Val Loss: 1.2258, Val Accuracy: 0.6875
Epoch 5396/10000, Train Loss: 1.1530, Train Accuracy: 0.7712, Val Loss: 1.2258, Val Accuracy: 0.6875
Epoch 5397/10000, Train Loss: 1.1431, Train Accuracy: 0.7712, Val Loss: 1.2259, Val Accuracy: 0.6875
Epoch 5398/10000, Train Loss: 1.1451, Train Accuracy: 0.7690, Val Loss: 1.2257, Val Accuracy: 0.6875
Epoch 5399/10000, Train Loss: 1.1510, Train Accuracy: 0.7578, Val Loss: 1.2258, Val Accuracy: 0.6875
Epoch 5400/10000, Train Loss: 1.1459, Train Accuracy: 0.7746, Val Loss: 1.2259, Val Accuracy: 0.6875
Epoch 5401/10000, Train Loss: 1.1381, Train Accuracy: 0.7801, Val Loss: 1.2262, Val Accuracy: 0.6875
Epoch 5402/10000, Train Loss: 1.1501, Train Accuracy: 0.7533, Val Loss: 1.2263, Val Accuracy: 0.6875
Epoch 5403/10000, Train Loss: 1.1380, Train Accuracy: 0.7734, Val Loss: 1.2263, Val Accuracy: 0.6830
Epoch 5404/10000, Train Loss: 1.1491, Train Accuracy: 0.7623, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5405/10000, Train Loss: 1.1530, Train Accuracy: 0.7623, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5406/10000, Train Loss: 1.1430, Train Accuracy: 0.7734, Val Loss: 1.2259, Val Accuracy: 0.6786
Epoch 5407/10000, Train Loss: 1.1427, Train Accuracy: 0.7701, Val Loss: 1.2260, Val Accuracy: 0.6786
Epoch 5408/10000, Train Loss: 1.1473, Train Accuracy: 0.7701, Val Loss: 1.2261, Val Accuracy: 0.6786
Epoch 5409/10000, Train Loss: 1.1431, Train Accuracy: 0.7701, Val Loss: 1.2263, Val Accuracy: 0.6786
Epoch 5410/10000, Train Loss: 1.1474, Train Accuracy: 0.7667, Val Loss: 1.2264, Val Accuracy: 0.6786
Epoch 5411/10000, Train Loss: 1.1442, Train Accuracy: 0.7768, Val Loss: 1.2263, Val Accuracy: 0.6786
Epoch 5412/10000, Train Loss: 1.1378, Train Accuracy: 0.7746, Val Loss: 1.2263, Val Accuracy: 0.6875
Epoch 5413/10000, Train Loss: 1.1519, Train Accuracy: 0.7623, Val Loss: 1.2262, Val Accuracy: 0.6875
Epoch 5414/10000, Train Loss: 1.1465, Train Accuracy: 0.7812, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5415/10000, Train Loss: 1.1534, Train Accuracy: 0.7623, Val Loss: 1.2260, Val Accuracy: 0.6875
Epoch 5416/10000, Train Loss: 1.1308, Train Accuracy: 0.7935, Val Loss: 1.2260, Val Accuracy: 0.6875
Epoch 5417/10000, Train Loss: 1.1423, Train Accuracy: 0.7734, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5418/10000, Train Loss: 1.1341, Train Accuracy: 0.7824, Val Loss: 1.2258, Val Accuracy: 0.6875
Epoch 5419/10000, Train Loss: 1.1408, Train Accuracy: 0.7790, Val Loss: 1.2260, Val Accuracy: 0.6875
Epoch 5420/10000, Train Loss: 1.1550, Train Accuracy: 0.7589, Val Loss: 1.2259, Val Accuracy: 0.6875
Epoch 5421/10000, Train Loss: 1.1325, Train Accuracy: 0.7958, Val Loss: 1.2260, Val Accuracy: 0.6875
Epoch 5422/10000, Train Loss: 1.1370, Train Accuracy: 0.7790, Val Loss: 1.2262, Val Accuracy: 0.6875
Epoch 5423/10000, Train Loss: 1.1525, Train Accuracy: 0.7656, Val Loss: 1.2260, Val Accuracy: 0.6875
Epoch 5424/10000, Train Loss: 1.1414, Train Accuracy: 0.7835, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5425/10000, Train Loss: 1.1474, Train Accuracy: 0.7723, Val Loss: 1.2259, Val Accuracy: 0.6875
Epoch 5426/10000, Train Loss: 1.1523, Train Accuracy: 0.7690, Val Loss: 1.2259, Val Accuracy: 0.6875
Epoch 5427/10000, Train Loss: 1.1484, Train Accuracy: 0.7746, Val Loss: 1.2259, Val Accuracy: 0.6830
Epoch 5428/10000, Train Loss: 1.1435, Train Accuracy: 0.7734, Val Loss: 1.2257, Val Accuracy: 0.6875
Epoch 5429/10000, Train Loss: 1.1439, Train Accuracy: 0.7812, Val Loss: 1.2259, Val Accuracy: 0.6830
Epoch 5430/10000, Train Loss: 1.1421, Train Accuracy: 0.7734, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5431/10000, Train Loss: 1.1529, Train Accuracy: 0.7556, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5432/10000, Train Loss: 1.1566, Train Accuracy: 0.7567, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5433/10000, Train Loss: 1.1493, Train Accuracy: 0.7679, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5434/10000, Train Loss: 1.1443, Train Accuracy: 0.7812, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5435/10000, Train Loss: 1.1471, Train Accuracy: 0.7712, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5436/10000, Train Loss: 1.1396, Train Accuracy: 0.7746, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5437/10000, Train Loss: 1.1323, Train Accuracy: 0.7801, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5438/10000, Train Loss: 1.1353, Train Accuracy: 0.7891, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5439/10000, Train Loss: 1.1512, Train Accuracy: 0.7667, Val Loss: 1.2264, Val Accuracy: 0.6830
Epoch 5440/10000, Train Loss: 1.1457, Train Accuracy: 0.7712, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5441/10000, Train Loss: 1.1471, Train Accuracy: 0.7656, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5442/10000, Train Loss: 1.1409, Train Accuracy: 0.7667, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5443/10000, Train Loss: 1.1355, Train Accuracy: 0.7801, Val Loss: 1.2260, Val Accuracy: 0.6830
Epoch 5444/10000, Train Loss: 1.1465, Train Accuracy: 0.7701, Val Loss: 1.2262, Val Accuracy: 0.6830
Epoch 5445/10000, Train Loss: 1.1355, Train Accuracy: 0.7768, Val Loss: 1.2261, Val Accuracy: 0.6830
Epoch 5446/10000, Train Loss: 1.1411, Train Accuracy: 0.7701, Val Loss: 1.2258, Val Accuracy: 0.6830
Epoch 5447/10000, Train Loss: 1.1444, Train Accuracy: 0.7746, Val Loss: 1.2256, Val Accuracy: 0.6830
Epoch 5448/10000, Train Loss: 1.1527, Train Accuracy: 0.7600, Val Loss: 1.2256, Val Accuracy: 0.6830
Epoch 5449/10000, Train Loss: 1.1374, Train Accuracy: 0.7757, Val Loss: 1.2257, Val Accuracy: 0.6830
Epoch 5450/10000, Train Loss: 1.1297, Train Accuracy: 0.7902, Val Loss: 1.2253, Val Accuracy: 0.6830
Epoch 5451/10000, Train Loss: 1.1485, Train Accuracy: 0.7667, Val Loss: 1.2252, Val Accuracy: 0.6830
Epoch 5452/10000, Train Loss: 1.1435, Train Accuracy: 0.7723, Val Loss: 1.2253, Val Accuracy: 0.6830
Epoch 5453/10000, Train Loss: 1.1359, Train Accuracy: 0.7835, Val Loss: 1.2252, Val Accuracy: 0.6830
Epoch 5454/10000, Train Loss: 1.1556, Train Accuracy: 0.7556, Val Loss: 1.2253, Val Accuracy: 0.6830
Epoch 5455/10000, Train Loss: 1.1407, Train Accuracy: 0.7846, Val Loss: 1.2251, Val Accuracy: 0.6875
Epoch 5456/10000, Train Loss: 1.1431, Train Accuracy: 0.7667, Val Loss: 1.2249, Val Accuracy: 0.6875
Epoch 5457/10000, Train Loss: 1.1365, Train Accuracy: 0.7879, Val Loss: 1.2250, Val Accuracy: 0.6920
Epoch 5458/10000, Train Loss: 1.1298, Train Accuracy: 0.7924, Val Loss: 1.2251, Val Accuracy: 0.6920
Epoch 5459/10000, Train Loss: 1.1509, Train Accuracy: 0.7645, Val Loss: 1.2248, Val Accuracy: 0.6920
Epoch 5460/10000, Train Loss: 1.1450, Train Accuracy: 0.7690, Val Loss: 1.2244, Val Accuracy: 0.6920
Epoch 5461/10000, Train Loss: 1.1451, Train Accuracy: 0.7734, Val Loss: 1.2245, Val Accuracy: 0.6875
Epoch 5462/10000, Train Loss: 1.1481, Train Accuracy: 0.7734, Val Loss: 1.2246, Val Accuracy: 0.6875
Epoch 5463/10000, Train Loss: 1.1424, Train Accuracy: 0.7801, Val Loss: 1.2246, Val Accuracy: 0.6875
Epoch 5464/10000, Train Loss: 1.1459, Train Accuracy: 0.7634, Val Loss: 1.2245, Val Accuracy: 0.6875
Epoch 5465/10000, Train Loss: 1.1426, Train Accuracy: 0.7790, Val Loss: 1.2244, Val Accuracy: 0.6875
Epoch 5466/10000, Train Loss: 1.1489, Train Accuracy: 0.7679, Val Loss: 1.2243, Val Accuracy: 0.6875
Epoch 5467/10000, Train Loss: 1.1416, Train Accuracy: 0.7690, Val Loss: 1.2244, Val Accuracy: 0.6875
Epoch 5468/10000, Train Loss: 1.1416, Train Accuracy: 0.7757, Val Loss: 1.2244, Val Accuracy: 0.6920
Epoch 5469/10000, Train Loss: 1.1416, Train Accuracy: 0.7712, Val Loss: 1.2244, Val Accuracy: 0.6830
Epoch 5470/10000, Train Loss: 1.1429, Train Accuracy: 0.7712, Val Loss: 1.2244, Val Accuracy: 0.6875
Epoch 5471/10000, Train Loss: 1.1409, Train Accuracy: 0.7734, Val Loss: 1.2244, Val Accuracy: 0.6875
Epoch 5472/10000, Train Loss: 1.1541, Train Accuracy: 0.7612, Val Loss: 1.2243, Val Accuracy: 0.6875
Epoch 5473/10000, Train Loss: 1.1434, Train Accuracy: 0.7679, Val Loss: 1.2242, Val Accuracy: 0.6830
Epoch 5474/10000, Train Loss: 1.1522, Train Accuracy: 0.7634, Val Loss: 1.2241, Val Accuracy: 0.6830
Epoch 5475/10000, Train Loss: 1.1429, Train Accuracy: 0.7712, Val Loss: 1.2238, Val Accuracy: 0.6875
Epoch 5476/10000, Train Loss: 1.1370, Train Accuracy: 0.7768, Val Loss: 1.2239, Val Accuracy: 0.6875
Epoch 5477/10000, Train Loss: 1.1475, Train Accuracy: 0.7746, Val Loss: 1.2237, Val Accuracy: 0.6875
Epoch 5478/10000, Train Loss: 1.1376, Train Accuracy: 0.7779, Val Loss: 1.2237, Val Accuracy: 0.6875
Epoch 5479/10000, Train Loss: 1.1455, Train Accuracy: 0.7645, Val Loss: 1.2235, Val Accuracy: 0.6875
Epoch 5480/10000, Train Loss: 1.1433, Train Accuracy: 0.7746, Val Loss: 1.2236, Val Accuracy: 0.6875
Epoch 5481/10000, Train Loss: 1.1464, Train Accuracy: 0.7645, Val Loss: 1.2235, Val Accuracy: 0.6920
Epoch 5482/10000, Train Loss: 1.1478, Train Accuracy: 0.7690, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5483/10000, Train Loss: 1.1391, Train Accuracy: 0.7768, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5484/10000, Train Loss: 1.1408, Train Accuracy: 0.7801, Val Loss: 1.2232, Val Accuracy: 0.6920
Epoch 5485/10000, Train Loss: 1.1385, Train Accuracy: 0.7868, Val Loss: 1.2230, Val Accuracy: 0.6920
Epoch 5486/10000, Train Loss: 1.1443, Train Accuracy: 0.7801, Val Loss: 1.2232, Val Accuracy: 0.6920
Epoch 5487/10000, Train Loss: 1.1441, Train Accuracy: 0.7812, Val Loss: 1.2232, Val Accuracy: 0.6920
Epoch 5488/10000, Train Loss: 1.1320, Train Accuracy: 0.7824, Val Loss: 1.2233, Val Accuracy: 0.6920
Epoch 5489/10000, Train Loss: 1.1362, Train Accuracy: 0.7801, Val Loss: 1.2233, Val Accuracy: 0.6920
Epoch 5490/10000, Train Loss: 1.1433, Train Accuracy: 0.7790, Val Loss: 1.2231, Val Accuracy: 0.6920
Epoch 5491/10000, Train Loss: 1.1463, Train Accuracy: 0.7701, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5492/10000, Train Loss: 1.1350, Train Accuracy: 0.7835, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5493/10000, Train Loss: 1.1404, Train Accuracy: 0.7701, Val Loss: 1.2229, Val Accuracy: 0.6875
Epoch 5494/10000, Train Loss: 1.1416, Train Accuracy: 0.7768, Val Loss: 1.2228, Val Accuracy: 0.6875
Epoch 5495/10000, Train Loss: 1.1361, Train Accuracy: 0.7790, Val Loss: 1.2229, Val Accuracy: 0.6875
Epoch 5496/10000, Train Loss: 1.1436, Train Accuracy: 0.7701, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5497/10000, Train Loss: 1.1473, Train Accuracy: 0.7679, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5498/10000, Train Loss: 1.1270, Train Accuracy: 0.7891, Val Loss: 1.2233, Val Accuracy: 0.6875
Epoch 5499/10000, Train Loss: 1.1364, Train Accuracy: 0.7790, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5500/10000, Train Loss: 1.1450, Train Accuracy: 0.7746, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5501/10000, Train Loss: 1.1578, Train Accuracy: 0.7522, Val Loss: 1.2230, Val Accuracy: 0.6875
Epoch 5502/10000, Train Loss: 1.1370, Train Accuracy: 0.7701, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5503/10000, Train Loss: 1.1419, Train Accuracy: 0.7768, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5504/10000, Train Loss: 1.1489, Train Accuracy: 0.7679, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5505/10000, Train Loss: 1.1477, Train Accuracy: 0.7634, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5506/10000, Train Loss: 1.1384, Train Accuracy: 0.7812, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5507/10000, Train Loss: 1.1421, Train Accuracy: 0.7734, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5508/10000, Train Loss: 1.1389, Train Accuracy: 0.7835, Val Loss: 1.2232, Val Accuracy: 0.6875
Epoch 5509/10000, Train Loss: 1.1413, Train Accuracy: 0.7757, Val Loss: 1.2235, Val Accuracy: 0.6875
Epoch 5510/10000, Train Loss: 1.1284, Train Accuracy: 0.7857, Val Loss: 1.2233, Val Accuracy: 0.6875
Epoch 5511/10000, Train Loss: 1.1350, Train Accuracy: 0.7768, Val Loss: 1.2236, Val Accuracy: 0.6875
Epoch 5512/10000, Train Loss: 1.1485, Train Accuracy: 0.7612, Val Loss: 1.2237, Val Accuracy: 0.6875
Epoch 5513/10000, Train Loss: 1.1404, Train Accuracy: 0.7835, Val Loss: 1.2237, Val Accuracy: 0.6875
Epoch 5514/10000, Train Loss: 1.1467, Train Accuracy: 0.7746, Val Loss: 1.2236, Val Accuracy: 0.6875
Epoch 5515/10000, Train Loss: 1.1488, Train Accuracy: 0.7645, Val Loss: 1.2235, Val Accuracy: 0.6875
Epoch 5516/10000, Train Loss: 1.1434, Train Accuracy: 0.7757, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5517/10000, Train Loss: 1.1446, Train Accuracy: 0.7656, Val Loss: 1.2233, Val Accuracy: 0.6875
Epoch 5518/10000, Train Loss: 1.1342, Train Accuracy: 0.7667, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5519/10000, Train Loss: 1.1375, Train Accuracy: 0.7857, Val Loss: 1.2231, Val Accuracy: 0.6875
Epoch 5520/10000, Train Loss: 1.1339, Train Accuracy: 0.7835, Val Loss: 1.2230, Val Accuracy: 0.6875
Epoch 5521/10000, Train Loss: 1.1339, Train Accuracy: 0.7868, Val Loss: 1.2229, Val Accuracy: 0.6875
Epoch 5522/10000, Train Loss: 1.1430, Train Accuracy: 0.7757, Val Loss: 1.2233, Val Accuracy: 0.6875
Epoch 5523/10000, Train Loss: 1.1340, Train Accuracy: 0.7846, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5524/10000, Train Loss: 1.1489, Train Accuracy: 0.7578, Val Loss: 1.2235, Val Accuracy: 0.6875
Epoch 5525/10000, Train Loss: 1.1399, Train Accuracy: 0.7746, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5526/10000, Train Loss: 1.1442, Train Accuracy: 0.7746, Val Loss: 1.2235, Val Accuracy: 0.6875
Epoch 5527/10000, Train Loss: 1.1333, Train Accuracy: 0.7801, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5528/10000, Train Loss: 1.1457, Train Accuracy: 0.7779, Val Loss: 1.2234, Val Accuracy: 0.6875
Epoch 5529/10000, Train Loss: 1.1402, Train Accuracy: 0.7679, Val Loss: 1.2233, Val Accuracy: 0.6875
Epoch 5530/10000, Train Loss: 1.1517, Train Accuracy: 0.7634, Val Loss: 1.2230, Val Accuracy: 0.6875
Epoch 5531/10000, Train Loss: 1.1467, Train Accuracy: 0.7723, Val Loss: 1.2228, Val Accuracy: 0.6875
Epoch 5532/10000, Train Loss: 1.1401, Train Accuracy: 0.7812, Val Loss: 1.2224, Val Accuracy: 0.6875
Epoch 5533/10000, Train Loss: 1.1412, Train Accuracy: 0.7779, Val Loss: 1.2222, Val Accuracy: 0.6875
Epoch 5534/10000, Train Loss: 1.1395, Train Accuracy: 0.7846, Val Loss: 1.2222, Val Accuracy: 0.6875
Epoch 5535/10000, Train Loss: 1.1342, Train Accuracy: 0.7824, Val Loss: 1.2222, Val Accuracy: 0.6875
Epoch 5536/10000, Train Loss: 1.1481, Train Accuracy: 0.7712, Val Loss: 1.2222, Val Accuracy: 0.6875
Epoch 5537/10000, Train Loss: 1.1369, Train Accuracy: 0.7868, Val Loss: 1.2221, Val Accuracy: 0.6875
Epoch 5538/10000, Train Loss: 1.1435, Train Accuracy: 0.7734, Val Loss: 1.2221, Val Accuracy: 0.6875
Epoch 5539/10000, Train Loss: 1.1431, Train Accuracy: 0.7701, Val Loss: 1.2219, Val Accuracy: 0.6875
Epoch 5540/10000, Train Loss: 1.1380, Train Accuracy: 0.7779, Val Loss: 1.2217, Val Accuracy: 0.6875
Epoch 5541/10000, Train Loss: 1.1507, Train Accuracy: 0.7600, Val Loss: 1.2218, Val Accuracy: 0.6875
Epoch 5542/10000, Train Loss: 1.1482, Train Accuracy: 0.7690, Val Loss: 1.2218, Val Accuracy: 0.6875
Epoch 5543/10000, Train Loss: 1.1466, Train Accuracy: 0.7690, Val Loss: 1.2215, Val Accuracy: 0.6875
Epoch 5544/10000, Train Loss: 1.1264, Train Accuracy: 0.7991, Val Loss: 1.2213, Val Accuracy: 0.6875
Epoch 5545/10000, Train Loss: 1.1496, Train Accuracy: 0.7612, Val Loss: 1.2208, Val Accuracy: 0.6875
Epoch 5546/10000, Train Loss: 1.1237, Train Accuracy: 0.7913, Val Loss: 1.2208, Val Accuracy: 0.6830
Epoch 5547/10000, Train Loss: 1.1373, Train Accuracy: 0.7812, Val Loss: 1.2207, Val Accuracy: 0.6830
Epoch 5548/10000, Train Loss: 1.1454, Train Accuracy: 0.7656, Val Loss: 1.2207, Val Accuracy: 0.6830
Epoch 5549/10000, Train Loss: 1.1465, Train Accuracy: 0.7712, Val Loss: 1.2208, Val Accuracy: 0.6830
Epoch 5550/10000, Train Loss: 1.1294, Train Accuracy: 0.7812, Val Loss: 1.2208, Val Accuracy: 0.6875
Epoch 5551/10000, Train Loss: 1.1358, Train Accuracy: 0.7801, Val Loss: 1.2207, Val Accuracy: 0.6875
Epoch 5552/10000, Train Loss: 1.1346, Train Accuracy: 0.7879, Val Loss: 1.2207, Val Accuracy: 0.6875
Epoch 5553/10000, Train Loss: 1.1428, Train Accuracy: 0.7790, Val Loss: 1.2206, Val Accuracy: 0.6875
Epoch 5554/10000, Train Loss: 1.1516, Train Accuracy: 0.7623, Val Loss: 1.2206, Val Accuracy: 0.6875
Epoch 5555/10000, Train Loss: 1.1402, Train Accuracy: 0.7746, Val Loss: 1.2207, Val Accuracy: 0.6875
Epoch 5556/10000, Train Loss: 1.1374, Train Accuracy: 0.7824, Val Loss: 1.2208, Val Accuracy: 0.6830
Epoch 5557/10000, Train Loss: 1.1325, Train Accuracy: 0.7801, Val Loss: 1.2206, Val Accuracy: 0.6875
Epoch 5558/10000, Train Loss: 1.1300, Train Accuracy: 0.7846, Val Loss: 1.2204, Val Accuracy: 0.6920
Epoch 5559/10000, Train Loss: 1.1472, Train Accuracy: 0.7623, Val Loss: 1.2206, Val Accuracy: 0.6875
Epoch 5560/10000, Train Loss: 1.1418, Train Accuracy: 0.7801, Val Loss: 1.2205, Val Accuracy: 0.6875
Epoch 5561/10000, Train Loss: 1.1371, Train Accuracy: 0.7779, Val Loss: 1.2203, Val Accuracy: 0.6875
Epoch 5562/10000, Train Loss: 1.1344, Train Accuracy: 0.7768, Val Loss: 1.2205, Val Accuracy: 0.6875
Epoch 5563/10000, Train Loss: 1.1269, Train Accuracy: 0.7902, Val Loss: 1.2205, Val Accuracy: 0.6920
Epoch 5564/10000, Train Loss: 1.1398, Train Accuracy: 0.7790, Val Loss: 1.2204, Val Accuracy: 0.6920
Epoch 5565/10000, Train Loss: 1.1392, Train Accuracy: 0.7768, Val Loss: 1.2205, Val Accuracy: 0.6920
Epoch 5566/10000, Train Loss: 1.1455, Train Accuracy: 0.7746, Val Loss: 1.2206, Val Accuracy: 0.6964
Epoch 5567/10000, Train Loss: 1.1372, Train Accuracy: 0.7712, Val Loss: 1.2206, Val Accuracy: 0.6964
Epoch 5568/10000, Train Loss: 1.1348, Train Accuracy: 0.7790, Val Loss: 1.2203, Val Accuracy: 0.6920
Epoch 5569/10000, Train Loss: 1.1382, Train Accuracy: 0.7868, Val Loss: 1.2201, Val Accuracy: 0.6920
Epoch 5570/10000, Train Loss: 1.1155, Train Accuracy: 0.8036, Val Loss: 1.2200, Val Accuracy: 0.6920
Epoch 5571/10000, Train Loss: 1.1357, Train Accuracy: 0.7846, Val Loss: 1.2199, Val Accuracy: 0.6920
Epoch 5572/10000, Train Loss: 1.1429, Train Accuracy: 0.7746, Val Loss: 1.2198, Val Accuracy: 0.6920
Epoch 5573/10000, Train Loss: 1.1354, Train Accuracy: 0.7801, Val Loss: 1.2197, Val Accuracy: 0.6920
Epoch 5574/10000, Train Loss: 1.1333, Train Accuracy: 0.7924, Val Loss: 1.2197, Val Accuracy: 0.6920
Epoch 5575/10000, Train Loss: 1.1453, Train Accuracy: 0.7712, Val Loss: 1.2196, Val Accuracy: 0.6920
Epoch 5576/10000, Train Loss: 1.1322, Train Accuracy: 0.7913, Val Loss: 1.2194, Val Accuracy: 0.6920
Epoch 5577/10000, Train Loss: 1.1465, Train Accuracy: 0.7679, Val Loss: 1.2196, Val Accuracy: 0.6920
Epoch 5578/10000, Train Loss: 1.1330, Train Accuracy: 0.7924, Val Loss: 1.2199, Val Accuracy: 0.6920
Epoch 5579/10000, Train Loss: 1.1381, Train Accuracy: 0.7723, Val Loss: 1.2197, Val Accuracy: 0.6920
Epoch 5580/10000, Train Loss: 1.1359, Train Accuracy: 0.7734, Val Loss: 1.2196, Val Accuracy: 0.6920
Epoch 5581/10000, Train Loss: 1.1292, Train Accuracy: 0.7980, Val Loss: 1.2194, Val Accuracy: 0.6964
Epoch 5582/10000, Train Loss: 1.1308, Train Accuracy: 0.7946, Val Loss: 1.2193, Val Accuracy: 0.6920
Epoch 5583/10000, Train Loss: 1.1385, Train Accuracy: 0.7768, Val Loss: 1.2194, Val Accuracy: 0.6920
Epoch 5584/10000, Train Loss: 1.1412, Train Accuracy: 0.7679, Val Loss: 1.2195, Val Accuracy: 0.6920
Epoch 5585/10000, Train Loss: 1.1294, Train Accuracy: 0.7902, Val Loss: 1.2192, Val Accuracy: 0.6920
Epoch 5586/10000, Train Loss: 1.1323, Train Accuracy: 0.7824, Val Loss: 1.2191, Val Accuracy: 0.6964
Epoch 5587/10000, Train Loss: 1.1366, Train Accuracy: 0.7812, Val Loss: 1.2191, Val Accuracy: 0.6964
Epoch 5588/10000, Train Loss: 1.1354, Train Accuracy: 0.7779, Val Loss: 1.2194, Val Accuracy: 0.6964
Epoch 5589/10000, Train Loss: 1.1355, Train Accuracy: 0.7757, Val Loss: 1.2195, Val Accuracy: 0.6920
Epoch 5590/10000, Train Loss: 1.1419, Train Accuracy: 0.7790, Val Loss: 1.2196, Val Accuracy: 0.6920
Epoch 5591/10000, Train Loss: 1.1399, Train Accuracy: 0.7779, Val Loss: 1.2198, Val Accuracy: 0.6920
Epoch 5592/10000, Train Loss: 1.1498, Train Accuracy: 0.7578, Val Loss: 1.2196, Val Accuracy: 0.6920
Epoch 5593/10000, Train Loss: 1.1425, Train Accuracy: 0.7734, Val Loss: 1.2196, Val Accuracy: 0.6964
Epoch 5594/10000, Train Loss: 1.1338, Train Accuracy: 0.7812, Val Loss: 1.2194, Val Accuracy: 0.6964
Epoch 5595/10000, Train Loss: 1.1330, Train Accuracy: 0.7868, Val Loss: 1.2195, Val Accuracy: 0.6964
Epoch 5596/10000, Train Loss: 1.1405, Train Accuracy: 0.7779, Val Loss: 1.2194, Val Accuracy: 0.6920
Epoch 5597/10000, Train Loss: 1.1306, Train Accuracy: 0.7891, Val Loss: 1.2192, Val Accuracy: 0.6920
Epoch 5598/10000, Train Loss: 1.1365, Train Accuracy: 0.7824, Val Loss: 1.2194, Val Accuracy: 0.6920
Epoch 5599/10000, Train Loss: 1.1361, Train Accuracy: 0.7757, Val Loss: 1.2191, Val Accuracy: 0.6920
Epoch 5600/10000, Train Loss: 1.1432, Train Accuracy: 0.7679, Val Loss: 1.2189, Val Accuracy: 0.6964
Epoch 5601/10000, Train Loss: 1.1340, Train Accuracy: 0.7801, Val Loss: 1.2189, Val Accuracy: 0.6964
Epoch 5602/10000, Train Loss: 1.1445, Train Accuracy: 0.7723, Val Loss: 1.2189, Val Accuracy: 0.6920
Epoch 5603/10000, Train Loss: 1.1312, Train Accuracy: 0.7891, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5604/10000, Train Loss: 1.1308, Train Accuracy: 0.7980, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5605/10000, Train Loss: 1.1303, Train Accuracy: 0.7891, Val Loss: 1.2185, Val Accuracy: 0.6964
Epoch 5606/10000, Train Loss: 1.1451, Train Accuracy: 0.7690, Val Loss: 1.2186, Val Accuracy: 0.6964
Epoch 5607/10000, Train Loss: 1.1417, Train Accuracy: 0.7757, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5608/10000, Train Loss: 1.1339, Train Accuracy: 0.7801, Val Loss: 1.2188, Val Accuracy: 0.6964
Epoch 5609/10000, Train Loss: 1.1317, Train Accuracy: 0.7935, Val Loss: 1.2188, Val Accuracy: 0.6920
Epoch 5610/10000, Train Loss: 1.1373, Train Accuracy: 0.7734, Val Loss: 1.2189, Val Accuracy: 0.6964
Epoch 5611/10000, Train Loss: 1.1300, Train Accuracy: 0.7913, Val Loss: 1.2188, Val Accuracy: 0.6964
Epoch 5612/10000, Train Loss: 1.1253, Train Accuracy: 0.7879, Val Loss: 1.2187, Val Accuracy: 0.6920
Epoch 5613/10000, Train Loss: 1.1462, Train Accuracy: 0.7757, Val Loss: 1.2190, Val Accuracy: 0.6964
Epoch 5614/10000, Train Loss: 1.1284, Train Accuracy: 0.7924, Val Loss: 1.2191, Val Accuracy: 0.6964
Epoch 5615/10000, Train Loss: 1.1399, Train Accuracy: 0.7757, Val Loss: 1.2189, Val Accuracy: 0.6964
Epoch 5616/10000, Train Loss: 1.1248, Train Accuracy: 0.7924, Val Loss: 1.2189, Val Accuracy: 0.6964
Epoch 5617/10000, Train Loss: 1.1340, Train Accuracy: 0.7779, Val Loss: 1.2188, Val Accuracy: 0.6964
Epoch 5618/10000, Train Loss: 1.1327, Train Accuracy: 0.7801, Val Loss: 1.2187, Val Accuracy: 0.6920
Epoch 5619/10000, Train Loss: 1.1376, Train Accuracy: 0.7812, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5620/10000, Train Loss: 1.1464, Train Accuracy: 0.7623, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5621/10000, Train Loss: 1.1471, Train Accuracy: 0.7567, Val Loss: 1.2186, Val Accuracy: 0.7009
Epoch 5622/10000, Train Loss: 1.1251, Train Accuracy: 0.7980, Val Loss: 1.2184, Val Accuracy: 0.7009
Epoch 5623/10000, Train Loss: 1.1422, Train Accuracy: 0.7779, Val Loss: 1.2187, Val Accuracy: 0.7009
Epoch 5624/10000, Train Loss: 1.1381, Train Accuracy: 0.7768, Val Loss: 1.2188, Val Accuracy: 0.7009
Epoch 5625/10000, Train Loss: 1.1343, Train Accuracy: 0.7835, Val Loss: 1.2188, Val Accuracy: 0.6964
Epoch 5626/10000, Train Loss: 1.1330, Train Accuracy: 0.7846, Val Loss: 1.2184, Val Accuracy: 0.6964
Epoch 5627/10000, Train Loss: 1.1331, Train Accuracy: 0.7757, Val Loss: 1.2184, Val Accuracy: 0.7009
Epoch 5628/10000, Train Loss: 1.1472, Train Accuracy: 0.7645, Val Loss: 1.2186, Val Accuracy: 0.6964
Epoch 5629/10000, Train Loss: 1.1398, Train Accuracy: 0.7801, Val Loss: 1.2186, Val Accuracy: 0.6964
Epoch 5630/10000, Train Loss: 1.1325, Train Accuracy: 0.7958, Val Loss: 1.2186, Val Accuracy: 0.6964
Epoch 5631/10000, Train Loss: 1.1355, Train Accuracy: 0.7790, Val Loss: 1.2185, Val Accuracy: 0.6964
Epoch 5632/10000, Train Loss: 1.1367, Train Accuracy: 0.7835, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5633/10000, Train Loss: 1.1368, Train Accuracy: 0.7723, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5634/10000, Train Loss: 1.1410, Train Accuracy: 0.7746, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5635/10000, Train Loss: 1.1298, Train Accuracy: 0.7868, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5636/10000, Train Loss: 1.1312, Train Accuracy: 0.7879, Val Loss: 1.2185, Val Accuracy: 0.6920
Epoch 5637/10000, Train Loss: 1.1337, Train Accuracy: 0.7812, Val Loss: 1.2184, Val Accuracy: 0.7009
Epoch 5638/10000, Train Loss: 1.1319, Train Accuracy: 0.7801, Val Loss: 1.2185, Val Accuracy: 0.7009
Epoch 5639/10000, Train Loss: 1.1349, Train Accuracy: 0.7846, Val Loss: 1.2184, Val Accuracy: 0.7009
Epoch 5640/10000, Train Loss: 1.1447, Train Accuracy: 0.7612, Val Loss: 1.2184, Val Accuracy: 0.7009
Epoch 5641/10000, Train Loss: 1.1305, Train Accuracy: 0.7891, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5642/10000, Train Loss: 1.1452, Train Accuracy: 0.7656, Val Loss: 1.2188, Val Accuracy: 0.7009
Epoch 5643/10000, Train Loss: 1.1416, Train Accuracy: 0.7746, Val Loss: 1.2188, Val Accuracy: 0.7009
Epoch 5644/10000, Train Loss: 1.1332, Train Accuracy: 0.7891, Val Loss: 1.2185, Val Accuracy: 0.6964
Epoch 5645/10000, Train Loss: 1.1313, Train Accuracy: 0.7991, Val Loss: 1.2184, Val Accuracy: 0.6964
Epoch 5646/10000, Train Loss: 1.1324, Train Accuracy: 0.7757, Val Loss: 1.2187, Val Accuracy: 0.6920
Epoch 5647/10000, Train Loss: 1.1420, Train Accuracy: 0.7645, Val Loss: 1.2186, Val Accuracy: 0.6920
Epoch 5648/10000, Train Loss: 1.1360, Train Accuracy: 0.7790, Val Loss: 1.2186, Val Accuracy: 0.6920
Epoch 5649/10000, Train Loss: 1.1314, Train Accuracy: 0.7835, Val Loss: 1.2187, Val Accuracy: 0.6964
Epoch 5650/10000, Train Loss: 1.1343, Train Accuracy: 0.7835, Val Loss: 1.2183, Val Accuracy: 0.6964
Epoch 5651/10000, Train Loss: 1.1224, Train Accuracy: 0.7935, Val Loss: 1.2181, Val Accuracy: 0.6964
Epoch 5652/10000, Train Loss: 1.1382, Train Accuracy: 0.7679, Val Loss: 1.2181, Val Accuracy: 0.6964
Epoch 5653/10000, Train Loss: 1.1253, Train Accuracy: 0.8002, Val Loss: 1.2181, Val Accuracy: 0.6920
Epoch 5654/10000, Train Loss: 1.1325, Train Accuracy: 0.7935, Val Loss: 1.2182, Val Accuracy: 0.6920
Epoch 5655/10000, Train Loss: 1.1319, Train Accuracy: 0.7835, Val Loss: 1.2180, Val Accuracy: 0.6920
Epoch 5656/10000, Train Loss: 1.1406, Train Accuracy: 0.7656, Val Loss: 1.2180, Val Accuracy: 0.6875
Epoch 5657/10000, Train Loss: 1.1413, Train Accuracy: 0.7712, Val Loss: 1.2180, Val Accuracy: 0.6920
Epoch 5658/10000, Train Loss: 1.1370, Train Accuracy: 0.7757, Val Loss: 1.2181, Val Accuracy: 0.7009
Epoch 5659/10000, Train Loss: 1.1390, Train Accuracy: 0.7790, Val Loss: 1.2182, Val Accuracy: 0.6920
Epoch 5660/10000, Train Loss: 1.1226, Train Accuracy: 0.7935, Val Loss: 1.2179, Val Accuracy: 0.6920
Epoch 5661/10000, Train Loss: 1.1272, Train Accuracy: 0.7980, Val Loss: 1.2178, Val Accuracy: 0.6875
Epoch 5662/10000, Train Loss: 1.1454, Train Accuracy: 0.7679, Val Loss: 1.2176, Val Accuracy: 0.6920
Epoch 5663/10000, Train Loss: 1.1331, Train Accuracy: 0.7779, Val Loss: 1.2178, Val Accuracy: 0.6920
Epoch 5664/10000, Train Loss: 1.1375, Train Accuracy: 0.7812, Val Loss: 1.2177, Val Accuracy: 0.6920
Epoch 5665/10000, Train Loss: 1.1389, Train Accuracy: 0.7835, Val Loss: 1.2177, Val Accuracy: 0.6920
Epoch 5666/10000, Train Loss: 1.1224, Train Accuracy: 0.8025, Val Loss: 1.2176, Val Accuracy: 0.6875
Epoch 5667/10000, Train Loss: 1.1333, Train Accuracy: 0.7779, Val Loss: 1.2174, Val Accuracy: 0.6920
Epoch 5668/10000, Train Loss: 1.1446, Train Accuracy: 0.7667, Val Loss: 1.2173, Val Accuracy: 0.6875
Epoch 5669/10000, Train Loss: 1.1256, Train Accuracy: 0.7935, Val Loss: 1.2172, Val Accuracy: 0.6875
Epoch 5670/10000, Train Loss: 1.1316, Train Accuracy: 0.7958, Val Loss: 1.2173, Val Accuracy: 0.6920
Epoch 5671/10000, Train Loss: 1.1191, Train Accuracy: 0.7991, Val Loss: 1.2171, Val Accuracy: 0.6964
Epoch 5672/10000, Train Loss: 1.1432, Train Accuracy: 0.7679, Val Loss: 1.2171, Val Accuracy: 0.6875
Epoch 5673/10000, Train Loss: 1.1292, Train Accuracy: 0.7891, Val Loss: 1.2173, Val Accuracy: 0.6875
Epoch 5674/10000, Train Loss: 1.1297, Train Accuracy: 0.7924, Val Loss: 1.2173, Val Accuracy: 0.6964
Epoch 5675/10000, Train Loss: 1.1397, Train Accuracy: 0.7723, Val Loss: 1.2172, Val Accuracy: 0.6964
Epoch 5676/10000, Train Loss: 1.1260, Train Accuracy: 0.7846, Val Loss: 1.2174, Val Accuracy: 0.6964
Epoch 5677/10000, Train Loss: 1.1365, Train Accuracy: 0.7790, Val Loss: 1.2173, Val Accuracy: 0.6964
Epoch 5678/10000, Train Loss: 1.1348, Train Accuracy: 0.7824, Val Loss: 1.2172, Val Accuracy: 0.6964
Epoch 5679/10000, Train Loss: 1.1350, Train Accuracy: 0.7835, Val Loss: 1.2172, Val Accuracy: 0.6964
Epoch 5680/10000, Train Loss: 1.1434, Train Accuracy: 0.7712, Val Loss: 1.2172, Val Accuracy: 0.6964
Epoch 5681/10000, Train Loss: 1.1357, Train Accuracy: 0.7779, Val Loss: 1.2171, Val Accuracy: 0.6875
Epoch 5682/10000, Train Loss: 1.1328, Train Accuracy: 0.7902, Val Loss: 1.2172, Val Accuracy: 0.6875
Epoch 5683/10000, Train Loss: 1.1273, Train Accuracy: 0.7924, Val Loss: 1.2169, Val Accuracy: 0.6920
Epoch 5684/10000, Train Loss: 1.1287, Train Accuracy: 0.7891, Val Loss: 1.2169, Val Accuracy: 0.6920
Epoch 5685/10000, Train Loss: 1.1292, Train Accuracy: 0.7868, Val Loss: 1.2167, Val Accuracy: 0.6920
Epoch 5686/10000, Train Loss: 1.1326, Train Accuracy: 0.7913, Val Loss: 1.2169, Val Accuracy: 0.6875
Epoch 5687/10000, Train Loss: 1.1493, Train Accuracy: 0.7578, Val Loss: 1.2169, Val Accuracy: 0.6920
Epoch 5688/10000, Train Loss: 1.1325, Train Accuracy: 0.7812, Val Loss: 1.2171, Val Accuracy: 0.6920
Epoch 5689/10000, Train Loss: 1.1330, Train Accuracy: 0.7879, Val Loss: 1.2171, Val Accuracy: 0.6920
Epoch 5690/10000, Train Loss: 1.1400, Train Accuracy: 0.7690, Val Loss: 1.2169, Val Accuracy: 0.6920
Epoch 5691/10000, Train Loss: 1.1243, Train Accuracy: 0.7980, Val Loss: 1.2168, Val Accuracy: 0.6920
Epoch 5692/10000, Train Loss: 1.1257, Train Accuracy: 0.7946, Val Loss: 1.2168, Val Accuracy: 0.6920
Epoch 5693/10000, Train Loss: 1.1383, Train Accuracy: 0.7734, Val Loss: 1.2167, Val Accuracy: 0.6920
Epoch 5694/10000, Train Loss: 1.1345, Train Accuracy: 0.7734, Val Loss: 1.2165, Val Accuracy: 0.6920
Epoch 5695/10000, Train Loss: 1.1445, Train Accuracy: 0.7712, Val Loss: 1.2163, Val Accuracy: 0.6920
Epoch 5696/10000, Train Loss: 1.1189, Train Accuracy: 0.7980, Val Loss: 1.2162, Val Accuracy: 0.6920
Epoch 5697/10000, Train Loss: 1.1321, Train Accuracy: 0.7868, Val Loss: 1.2165, Val Accuracy: 0.6920
Epoch 5698/10000, Train Loss: 1.1225, Train Accuracy: 0.7980, Val Loss: 1.2162, Val Accuracy: 0.6920
Epoch 5699/10000, Train Loss: 1.1304, Train Accuracy: 0.7902, Val Loss: 1.2161, Val Accuracy: 0.6964
Epoch 5700/10000, Train Loss: 1.1297, Train Accuracy: 0.7902, Val Loss: 1.2160, Val Accuracy: 0.6964
Epoch 5701/10000, Train Loss: 1.1364, Train Accuracy: 0.7824, Val Loss: 1.2159, Val Accuracy: 0.6920
Epoch 5702/10000, Train Loss: 1.1307, Train Accuracy: 0.7958, Val Loss: 1.2156, Val Accuracy: 0.6920
Epoch 5703/10000, Train Loss: 1.1192, Train Accuracy: 0.8069, Val Loss: 1.2157, Val Accuracy: 0.6920
Epoch 5704/10000, Train Loss: 1.1291, Train Accuracy: 0.7868, Val Loss: 1.2156, Val Accuracy: 0.6920
Epoch 5705/10000, Train Loss: 1.1339, Train Accuracy: 0.7790, Val Loss: 1.2157, Val Accuracy: 0.6920
Epoch 5706/10000, Train Loss: 1.1411, Train Accuracy: 0.7656, Val Loss: 1.2155, Val Accuracy: 0.6920
Epoch 5707/10000, Train Loss: 1.1333, Train Accuracy: 0.7723, Val Loss: 1.2153, Val Accuracy: 0.6920
Epoch 5708/10000, Train Loss: 1.1380, Train Accuracy: 0.7779, Val Loss: 1.2156, Val Accuracy: 0.6920
Epoch 5709/10000, Train Loss: 1.1305, Train Accuracy: 0.7846, Val Loss: 1.2155, Val Accuracy: 0.6920
Epoch 5710/10000, Train Loss: 1.1230, Train Accuracy: 0.7980, Val Loss: 1.2155, Val Accuracy: 0.6920
Epoch 5711/10000, Train Loss: 1.1250, Train Accuracy: 0.7969, Val Loss: 1.2153, Val Accuracy: 0.6920
Epoch 5712/10000, Train Loss: 1.1395, Train Accuracy: 0.7723, Val Loss: 1.2155, Val Accuracy: 0.6920
Epoch 5713/10000, Train Loss: 1.1349, Train Accuracy: 0.7734, Val Loss: 1.2157, Val Accuracy: 0.6920
Epoch 5714/10000, Train Loss: 1.1253, Train Accuracy: 0.7879, Val Loss: 1.2154, Val Accuracy: 0.6920
Epoch 5715/10000, Train Loss: 1.1412, Train Accuracy: 0.7746, Val Loss: 1.2155, Val Accuracy: 0.6920
Epoch 5716/10000, Train Loss: 1.1261, Train Accuracy: 0.7935, Val Loss: 1.2151, Val Accuracy: 0.6920
Epoch 5717/10000, Train Loss: 1.1325, Train Accuracy: 0.7868, Val Loss: 1.2153, Val Accuracy: 0.6964
Epoch 5718/10000, Train Loss: 1.1304, Train Accuracy: 0.7801, Val Loss: 1.2154, Val Accuracy: 0.6920
Epoch 5719/10000, Train Loss: 1.1353, Train Accuracy: 0.7857, Val Loss: 1.2152, Val Accuracy: 0.6920
Epoch 5720/10000, Train Loss: 1.1259, Train Accuracy: 0.7969, Val Loss: 1.2150, Val Accuracy: 0.6964
Epoch 5721/10000, Train Loss: 1.1242, Train Accuracy: 0.7902, Val Loss: 1.2150, Val Accuracy: 0.6964
Epoch 5722/10000, Train Loss: 1.1301, Train Accuracy: 0.7790, Val Loss: 1.2150, Val Accuracy: 0.7009
Epoch 5723/10000, Train Loss: 1.1360, Train Accuracy: 0.7835, Val Loss: 1.2148, Val Accuracy: 0.7009
Epoch 5724/10000, Train Loss: 1.1299, Train Accuracy: 0.7857, Val Loss: 1.2148, Val Accuracy: 0.7009
Epoch 5725/10000, Train Loss: 1.1263, Train Accuracy: 0.7879, Val Loss: 1.2148, Val Accuracy: 0.7009
Epoch 5726/10000, Train Loss: 1.1436, Train Accuracy: 0.7712, Val Loss: 1.2148, Val Accuracy: 0.7009
Epoch 5727/10000, Train Loss: 1.1280, Train Accuracy: 0.7902, Val Loss: 1.2148, Val Accuracy: 0.7009
Epoch 5728/10000, Train Loss: 1.1344, Train Accuracy: 0.7790, Val Loss: 1.2148, Val Accuracy: 0.6964
Epoch 5729/10000, Train Loss: 1.1248, Train Accuracy: 0.7902, Val Loss: 1.2145, Val Accuracy: 0.7009
Epoch 5730/10000, Train Loss: 1.1232, Train Accuracy: 0.7935, Val Loss: 1.2142, Val Accuracy: 0.7009
Epoch 5731/10000, Train Loss: 1.1226, Train Accuracy: 0.7991, Val Loss: 1.2143, Val Accuracy: 0.7009
Epoch 5732/10000, Train Loss: 1.1227, Train Accuracy: 0.7969, Val Loss: 1.2143, Val Accuracy: 0.6964
Epoch 5733/10000, Train Loss: 1.1333, Train Accuracy: 0.7734, Val Loss: 1.2140, Val Accuracy: 0.7009
Epoch 5734/10000, Train Loss: 1.1319, Train Accuracy: 0.7868, Val Loss: 1.2144, Val Accuracy: 0.7009
Epoch 5735/10000, Train Loss: 1.1396, Train Accuracy: 0.7712, Val Loss: 1.2143, Val Accuracy: 0.7009
Epoch 5736/10000, Train Loss: 1.1352, Train Accuracy: 0.7801, Val Loss: 1.2144, Val Accuracy: 0.6964
Epoch 5737/10000, Train Loss: 1.1345, Train Accuracy: 0.7835, Val Loss: 1.2146, Val Accuracy: 0.6964
Epoch 5738/10000, Train Loss: 1.1244, Train Accuracy: 0.7891, Val Loss: 1.2147, Val Accuracy: 0.6964
Epoch 5739/10000, Train Loss: 1.1429, Train Accuracy: 0.7712, Val Loss: 1.2149, Val Accuracy: 0.6964
Epoch 5740/10000, Train Loss: 1.1338, Train Accuracy: 0.7824, Val Loss: 1.2148, Val Accuracy: 0.6964
Epoch 5741/10000, Train Loss: 1.1234, Train Accuracy: 0.7935, Val Loss: 1.2148, Val Accuracy: 0.6964
Epoch 5742/10000, Train Loss: 1.1230, Train Accuracy: 0.8002, Val Loss: 1.2147, Val Accuracy: 0.6964
Epoch 5743/10000, Train Loss: 1.1261, Train Accuracy: 0.7891, Val Loss: 1.2146, Val Accuracy: 0.6964
Epoch 5744/10000, Train Loss: 1.1367, Train Accuracy: 0.7779, Val Loss: 1.2145, Val Accuracy: 0.6964
Epoch 5745/10000, Train Loss: 1.1344, Train Accuracy: 0.7757, Val Loss: 1.2143, Val Accuracy: 0.6964
Epoch 5746/10000, Train Loss: 1.1185, Train Accuracy: 0.8013, Val Loss: 1.2141, Val Accuracy: 0.6964
Epoch 5747/10000, Train Loss: 1.1427, Train Accuracy: 0.7656, Val Loss: 1.2142, Val Accuracy: 0.6964
Epoch 5748/10000, Train Loss: 1.1290, Train Accuracy: 0.7879, Val Loss: 1.2143, Val Accuracy: 0.6964
Epoch 5749/10000, Train Loss: 1.1392, Train Accuracy: 0.7757, Val Loss: 1.2142, Val Accuracy: 0.6964
Epoch 5750/10000, Train Loss: 1.1310, Train Accuracy: 0.7824, Val Loss: 1.2140, Val Accuracy: 0.6964
Epoch 5751/10000, Train Loss: 1.1345, Train Accuracy: 0.7768, Val Loss: 1.2137, Val Accuracy: 0.6964
Epoch 5752/10000, Train Loss: 1.1308, Train Accuracy: 0.7868, Val Loss: 1.2136, Val Accuracy: 0.6964
Epoch 5753/10000, Train Loss: 1.1209, Train Accuracy: 0.7913, Val Loss: 1.2132, Val Accuracy: 0.6964
Epoch 5754/10000, Train Loss: 1.1297, Train Accuracy: 0.7824, Val Loss: 1.2133, Val Accuracy: 0.7009
Epoch 5755/10000, Train Loss: 1.1184, Train Accuracy: 0.7969, Val Loss: 1.2131, Val Accuracy: 0.7009
Epoch 5756/10000, Train Loss: 1.1362, Train Accuracy: 0.7734, Val Loss: 1.2132, Val Accuracy: 0.6964
Epoch 5757/10000, Train Loss: 1.1346, Train Accuracy: 0.7790, Val Loss: 1.2129, Val Accuracy: 0.7009
Epoch 5758/10000, Train Loss: 1.1279, Train Accuracy: 0.7857, Val Loss: 1.2129, Val Accuracy: 0.7009
Epoch 5759/10000, Train Loss: 1.1303, Train Accuracy: 0.7824, Val Loss: 1.2130, Val Accuracy: 0.7009
Epoch 5760/10000, Train Loss: 1.1265, Train Accuracy: 0.7913, Val Loss: 1.2130, Val Accuracy: 0.7009
Epoch 5761/10000, Train Loss: 1.1211, Train Accuracy: 0.7935, Val Loss: 1.2127, Val Accuracy: 0.7009
Epoch 5762/10000, Train Loss: 1.1314, Train Accuracy: 0.7935, Val Loss: 1.2127, Val Accuracy: 0.7009
Epoch 5763/10000, Train Loss: 1.1204, Train Accuracy: 0.7935, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5764/10000, Train Loss: 1.1417, Train Accuracy: 0.7667, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5765/10000, Train Loss: 1.1207, Train Accuracy: 0.7913, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5766/10000, Train Loss: 1.1379, Train Accuracy: 0.7768, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5767/10000, Train Loss: 1.1337, Train Accuracy: 0.7824, Val Loss: 1.2123, Val Accuracy: 0.7009
Epoch 5768/10000, Train Loss: 1.1314, Train Accuracy: 0.7812, Val Loss: 1.2125, Val Accuracy: 0.7009
Epoch 5769/10000, Train Loss: 1.1172, Train Accuracy: 0.8025, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5770/10000, Train Loss: 1.1337, Train Accuracy: 0.7801, Val Loss: 1.2125, Val Accuracy: 0.7009
Epoch 5771/10000, Train Loss: 1.1244, Train Accuracy: 0.7935, Val Loss: 1.2123, Val Accuracy: 0.7009
Epoch 5772/10000, Train Loss: 1.1307, Train Accuracy: 0.7757, Val Loss: 1.2121, Val Accuracy: 0.7009
Epoch 5773/10000, Train Loss: 1.1300, Train Accuracy: 0.7812, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5774/10000, Train Loss: 1.1284, Train Accuracy: 0.7902, Val Loss: 1.2122, Val Accuracy: 0.7009
Epoch 5775/10000, Train Loss: 1.1221, Train Accuracy: 0.7946, Val Loss: 1.2122, Val Accuracy: 0.7009
Epoch 5776/10000, Train Loss: 1.1222, Train Accuracy: 0.7913, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5777/10000, Train Loss: 1.1413, Train Accuracy: 0.7656, Val Loss: 1.2124, Val Accuracy: 0.7009
Epoch 5778/10000, Train Loss: 1.1313, Train Accuracy: 0.7868, Val Loss: 1.2124, Val Accuracy: 0.7054
Epoch 5779/10000, Train Loss: 1.1266, Train Accuracy: 0.7980, Val Loss: 1.2126, Val Accuracy: 0.7009
Epoch 5780/10000, Train Loss: 1.1245, Train Accuracy: 0.7924, Val Loss: 1.2125, Val Accuracy: 0.7009
Epoch 5781/10000, Train Loss: 1.1364, Train Accuracy: 0.7790, Val Loss: 1.2122, Val Accuracy: 0.7009
Epoch 5782/10000, Train Loss: 1.1230, Train Accuracy: 0.7913, Val Loss: 1.2122, Val Accuracy: 0.7009
Epoch 5783/10000, Train Loss: 1.1190, Train Accuracy: 0.8013, Val Loss: 1.2122, Val Accuracy: 0.7009
Epoch 5784/10000, Train Loss: 1.1217, Train Accuracy: 0.7935, Val Loss: 1.2121, Val Accuracy: 0.7054
Epoch 5785/10000, Train Loss: 1.1262, Train Accuracy: 0.7868, Val Loss: 1.2120, Val Accuracy: 0.7054
Epoch 5786/10000, Train Loss: 1.1161, Train Accuracy: 0.8036, Val Loss: 1.2119, Val Accuracy: 0.7009
Epoch 5787/10000, Train Loss: 1.1306, Train Accuracy: 0.7790, Val Loss: 1.2118, Val Accuracy: 0.7009
Epoch 5788/10000, Train Loss: 1.1210, Train Accuracy: 0.8013, Val Loss: 1.2117, Val Accuracy: 0.7054
Epoch 5789/10000, Train Loss: 1.1354, Train Accuracy: 0.7746, Val Loss: 1.2115, Val Accuracy: 0.7054
Epoch 5790/10000, Train Loss: 1.1290, Train Accuracy: 0.7891, Val Loss: 1.2115, Val Accuracy: 0.7054
Epoch 5791/10000, Train Loss: 1.1428, Train Accuracy: 0.7723, Val Loss: 1.2117, Val Accuracy: 0.7054
Epoch 5792/10000, Train Loss: 1.1196, Train Accuracy: 0.7969, Val Loss: 1.2118, Val Accuracy: 0.7054
Epoch 5793/10000, Train Loss: 1.1275, Train Accuracy: 0.7879, Val Loss: 1.2118, Val Accuracy: 0.7054
Epoch 5794/10000, Train Loss: 1.1303, Train Accuracy: 0.7790, Val Loss: 1.2117, Val Accuracy: 0.7054
Epoch 5795/10000, Train Loss: 1.1288, Train Accuracy: 0.7935, Val Loss: 1.2118, Val Accuracy: 0.7009
Epoch 5796/10000, Train Loss: 1.1289, Train Accuracy: 0.7790, Val Loss: 1.2117, Val Accuracy: 0.7054
Epoch 5797/10000, Train Loss: 1.1340, Train Accuracy: 0.7801, Val Loss: 1.2119, Val Accuracy: 0.7054
Epoch 5798/10000, Train Loss: 1.1336, Train Accuracy: 0.7812, Val Loss: 1.2116, Val Accuracy: 0.7054
Epoch 5799/10000, Train Loss: 1.1315, Train Accuracy: 0.7801, Val Loss: 1.2113, Val Accuracy: 0.7054
Epoch 5800/10000, Train Loss: 1.1419, Train Accuracy: 0.7612, Val Loss: 1.2113, Val Accuracy: 0.7054
Epoch 5801/10000, Train Loss: 1.1347, Train Accuracy: 0.7801, Val Loss: 1.2114, Val Accuracy: 0.7054
Epoch 5802/10000, Train Loss: 1.1228, Train Accuracy: 0.7991, Val Loss: 1.2114, Val Accuracy: 0.7054
Epoch 5803/10000, Train Loss: 1.1181, Train Accuracy: 0.8002, Val Loss: 1.2113, Val Accuracy: 0.7054
Epoch 5804/10000, Train Loss: 1.1265, Train Accuracy: 0.7891, Val Loss: 1.2114, Val Accuracy: 0.7054
Epoch 5805/10000, Train Loss: 1.1394, Train Accuracy: 0.7768, Val Loss: 1.2112, Val Accuracy: 0.7054
Epoch 5806/10000, Train Loss: 1.1213, Train Accuracy: 0.7980, Val Loss: 1.2112, Val Accuracy: 0.7054
Epoch 5807/10000, Train Loss: 1.1343, Train Accuracy: 0.7812, Val Loss: 1.2113, Val Accuracy: 0.7054
Epoch 5808/10000, Train Loss: 1.1303, Train Accuracy: 0.7857, Val Loss: 1.2112, Val Accuracy: 0.7054
Epoch 5809/10000, Train Loss: 1.1251, Train Accuracy: 0.7946, Val Loss: 1.2112, Val Accuracy: 0.7054
Epoch 5810/10000, Train Loss: 1.1209, Train Accuracy: 0.8025, Val Loss: 1.2111, Val Accuracy: 0.7054
Epoch 5811/10000, Train Loss: 1.1180, Train Accuracy: 0.7991, Val Loss: 1.2112, Val Accuracy: 0.7054
Epoch 5812/10000, Train Loss: 1.1279, Train Accuracy: 0.7857, Val Loss: 1.2110, Val Accuracy: 0.7054
Epoch 5813/10000, Train Loss: 1.1229, Train Accuracy: 0.7991, Val Loss: 1.2111, Val Accuracy: 0.7054
Epoch 5814/10000, Train Loss: 1.1259, Train Accuracy: 0.7812, Val Loss: 1.2109, Val Accuracy: 0.7054
Epoch 5815/10000, Train Loss: 1.1352, Train Accuracy: 0.7801, Val Loss: 1.2108, Val Accuracy: 0.7054
Epoch 5816/10000, Train Loss: 1.1317, Train Accuracy: 0.7790, Val Loss: 1.2108, Val Accuracy: 0.7054
Epoch 5817/10000, Train Loss: 1.1364, Train Accuracy: 0.7757, Val Loss: 1.2107, Val Accuracy: 0.7054
Epoch 5818/10000, Train Loss: 1.1192, Train Accuracy: 0.7991, Val Loss: 1.2105, Val Accuracy: 0.7054
Epoch 5819/10000, Train Loss: 1.1299, Train Accuracy: 0.7958, Val Loss: 1.2107, Val Accuracy: 0.7054
Epoch 5820/10000, Train Loss: 1.1260, Train Accuracy: 0.7846, Val Loss: 1.2107, Val Accuracy: 0.7054
Epoch 5821/10000, Train Loss: 1.1354, Train Accuracy: 0.7712, Val Loss: 1.2109, Val Accuracy: 0.7098
Epoch 5822/10000, Train Loss: 1.1231, Train Accuracy: 0.7991, Val Loss: 1.2109, Val Accuracy: 0.7098
Epoch 5823/10000, Train Loss: 1.1373, Train Accuracy: 0.7734, Val Loss: 1.2108, Val Accuracy: 0.7054
Epoch 5824/10000, Train Loss: 1.1216, Train Accuracy: 0.7958, Val Loss: 1.2109, Val Accuracy: 0.7098
Epoch 5825/10000, Train Loss: 1.1273, Train Accuracy: 0.7868, Val Loss: 1.2109, Val Accuracy: 0.7098
Epoch 5826/10000, Train Loss: 1.1181, Train Accuracy: 0.8025, Val Loss: 1.2106, Val Accuracy: 0.7054
Epoch 5827/10000, Train Loss: 1.1279, Train Accuracy: 0.7924, Val Loss: 1.2105, Val Accuracy: 0.7098
Epoch 5828/10000, Train Loss: 1.1386, Train Accuracy: 0.7812, Val Loss: 1.2104, Val Accuracy: 0.7098
Epoch 5829/10000, Train Loss: 1.1303, Train Accuracy: 0.7924, Val Loss: 1.2100, Val Accuracy: 0.7098
Epoch 5830/10000, Train Loss: 1.1265, Train Accuracy: 0.7935, Val Loss: 1.2099, Val Accuracy: 0.7098
Epoch 5831/10000, Train Loss: 1.1280, Train Accuracy: 0.7891, Val Loss: 1.2096, Val Accuracy: 0.7098
Epoch 5832/10000, Train Loss: 1.1245, Train Accuracy: 0.7857, Val Loss: 1.2095, Val Accuracy: 0.7098
Epoch 5833/10000, Train Loss: 1.1300, Train Accuracy: 0.7879, Val Loss: 1.2096, Val Accuracy: 0.7098
Epoch 5834/10000, Train Loss: 1.1337, Train Accuracy: 0.7824, Val Loss: 1.2098, Val Accuracy: 0.7098
Epoch 5835/10000, Train Loss: 1.1393, Train Accuracy: 0.7712, Val Loss: 1.2098, Val Accuracy: 0.7098
Epoch 5836/10000, Train Loss: 1.1224, Train Accuracy: 0.7879, Val Loss: 1.2099, Val Accuracy: 0.7098
Epoch 5837/10000, Train Loss: 1.1276, Train Accuracy: 0.7824, Val Loss: 1.2099, Val Accuracy: 0.7054
Epoch 5838/10000, Train Loss: 1.1300, Train Accuracy: 0.7868, Val Loss: 1.2100, Val Accuracy: 0.7054
Epoch 5839/10000, Train Loss: 1.1314, Train Accuracy: 0.7935, Val Loss: 1.2099, Val Accuracy: 0.7054
Epoch 5840/10000, Train Loss: 1.1201, Train Accuracy: 0.7902, Val Loss: 1.2101, Val Accuracy: 0.7009
Epoch 5841/10000, Train Loss: 1.1257, Train Accuracy: 0.8013, Val Loss: 1.2100, Val Accuracy: 0.7009
Epoch 5842/10000, Train Loss: 1.1230, Train Accuracy: 0.8036, Val Loss: 1.2099, Val Accuracy: 0.7009
Epoch 5843/10000, Train Loss: 1.1207, Train Accuracy: 0.7969, Val Loss: 1.2097, Val Accuracy: 0.7054
Epoch 5844/10000, Train Loss: 1.1271, Train Accuracy: 0.7868, Val Loss: 1.2097, Val Accuracy: 0.7054
Epoch 5845/10000, Train Loss: 1.1212, Train Accuracy: 0.7924, Val Loss: 1.2096, Val Accuracy: 0.7098
Epoch 5846/10000, Train Loss: 1.1298, Train Accuracy: 0.7924, Val Loss: 1.2095, Val Accuracy: 0.7098
Epoch 5847/10000, Train Loss: 1.1309, Train Accuracy: 0.7801, Val Loss: 1.2093, Val Accuracy: 0.7098
Epoch 5848/10000, Train Loss: 1.1325, Train Accuracy: 0.7812, Val Loss: 1.2092, Val Accuracy: 0.7054
Epoch 5849/10000, Train Loss: 1.1218, Train Accuracy: 0.7924, Val Loss: 1.2092, Val Accuracy: 0.7098
Epoch 5850/10000, Train Loss: 1.1189, Train Accuracy: 0.7969, Val Loss: 1.2091, Val Accuracy: 0.7098
Epoch 5851/10000, Train Loss: 1.1283, Train Accuracy: 0.7846, Val Loss: 1.2090, Val Accuracy: 0.7098
Epoch 5852/10000, Train Loss: 1.1276, Train Accuracy: 0.7935, Val Loss: 1.2088, Val Accuracy: 0.7098
Epoch 5853/10000, Train Loss: 1.1310, Train Accuracy: 0.7801, Val Loss: 1.2091, Val Accuracy: 0.7098
Epoch 5854/10000, Train Loss: 1.1329, Train Accuracy: 0.7790, Val Loss: 1.2091, Val Accuracy: 0.7098
Epoch 5855/10000, Train Loss: 1.1459, Train Accuracy: 0.7690, Val Loss: 1.2093, Val Accuracy: 0.7098
Epoch 5856/10000, Train Loss: 1.1202, Train Accuracy: 0.7935, Val Loss: 1.2091, Val Accuracy: 0.7098
Epoch 5857/10000, Train Loss: 1.1190, Train Accuracy: 0.7946, Val Loss: 1.2093, Val Accuracy: 0.7098
Epoch 5858/10000, Train Loss: 1.1248, Train Accuracy: 0.7868, Val Loss: 1.2093, Val Accuracy: 0.7054
Epoch 5859/10000, Train Loss: 1.1257, Train Accuracy: 0.7868, Val Loss: 1.2091, Val Accuracy: 0.7054
Epoch 5860/10000, Train Loss: 1.1355, Train Accuracy: 0.7779, Val Loss: 1.2087, Val Accuracy: 0.7054
Epoch 5861/10000, Train Loss: 1.1174, Train Accuracy: 0.7958, Val Loss: 1.2087, Val Accuracy: 0.7054
Epoch 5862/10000, Train Loss: 1.1190, Train Accuracy: 0.7935, Val Loss: 1.2090, Val Accuracy: 0.7054
Epoch 5863/10000, Train Loss: 1.1387, Train Accuracy: 0.7734, Val Loss: 1.2091, Val Accuracy: 0.7054
Epoch 5864/10000, Train Loss: 1.1298, Train Accuracy: 0.7891, Val Loss: 1.2092, Val Accuracy: 0.7054
Epoch 5865/10000, Train Loss: 1.1384, Train Accuracy: 0.7712, Val Loss: 1.2093, Val Accuracy: 0.7054
Epoch 5866/10000, Train Loss: 1.1255, Train Accuracy: 0.7946, Val Loss: 1.2092, Val Accuracy: 0.7054
Epoch 5867/10000, Train Loss: 1.1273, Train Accuracy: 0.7768, Val Loss: 1.2094, Val Accuracy: 0.7054
Epoch 5868/10000, Train Loss: 1.1259, Train Accuracy: 0.7891, Val Loss: 1.2092, Val Accuracy: 0.7054
Epoch 5869/10000, Train Loss: 1.1241, Train Accuracy: 0.7946, Val Loss: 1.2086, Val Accuracy: 0.7054
Epoch 5870/10000, Train Loss: 1.1283, Train Accuracy: 0.7891, Val Loss: 1.2088, Val Accuracy: 0.7054
Epoch 5871/10000, Train Loss: 1.1250, Train Accuracy: 0.7924, Val Loss: 1.2089, Val Accuracy: 0.7054
Epoch 5872/10000, Train Loss: 1.1365, Train Accuracy: 0.7746, Val Loss: 1.2087, Val Accuracy: 0.7054
Epoch 5873/10000, Train Loss: 1.1336, Train Accuracy: 0.7835, Val Loss: 1.2085, Val Accuracy: 0.7054
Epoch 5874/10000, Train Loss: 1.1299, Train Accuracy: 0.7757, Val Loss: 1.2087, Val Accuracy: 0.7054
Epoch 5875/10000, Train Loss: 1.1331, Train Accuracy: 0.7846, Val Loss: 1.2085, Val Accuracy: 0.7054
Epoch 5876/10000, Train Loss: 1.1332, Train Accuracy: 0.7835, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5877/10000, Train Loss: 1.1164, Train Accuracy: 0.7991, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5878/10000, Train Loss: 1.1229, Train Accuracy: 0.7924, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5879/10000, Train Loss: 1.1191, Train Accuracy: 0.7946, Val Loss: 1.2085, Val Accuracy: 0.7009
Epoch 5880/10000, Train Loss: 1.1188, Train Accuracy: 0.7891, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5881/10000, Train Loss: 1.1398, Train Accuracy: 0.7679, Val Loss: 1.2085, Val Accuracy: 0.7009
Epoch 5882/10000, Train Loss: 1.1195, Train Accuracy: 0.7924, Val Loss: 1.2087, Val Accuracy: 0.7009
Epoch 5883/10000, Train Loss: 1.1240, Train Accuracy: 0.7902, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5884/10000, Train Loss: 1.1303, Train Accuracy: 0.7846, Val Loss: 1.2086, Val Accuracy: 0.7009
Epoch 5885/10000, Train Loss: 1.1361, Train Accuracy: 0.7824, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5886/10000, Train Loss: 1.1117, Train Accuracy: 0.8025, Val Loss: 1.2079, Val Accuracy: 0.7009
Epoch 5887/10000, Train Loss: 1.1271, Train Accuracy: 0.7846, Val Loss: 1.2079, Val Accuracy: 0.7009
Epoch 5888/10000, Train Loss: 1.1277, Train Accuracy: 0.7857, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5889/10000, Train Loss: 1.1315, Train Accuracy: 0.7902, Val Loss: 1.2083, Val Accuracy: 0.7009
Epoch 5890/10000, Train Loss: 1.1238, Train Accuracy: 0.7891, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5891/10000, Train Loss: 1.1215, Train Accuracy: 0.7958, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5892/10000, Train Loss: 1.1299, Train Accuracy: 0.7868, Val Loss: 1.2080, Val Accuracy: 0.7009
Epoch 5893/10000, Train Loss: 1.1318, Train Accuracy: 0.7801, Val Loss: 1.2080, Val Accuracy: 0.7009
Epoch 5894/10000, Train Loss: 1.1390, Train Accuracy: 0.7701, Val Loss: 1.2080, Val Accuracy: 0.7009
Epoch 5895/10000, Train Loss: 1.1249, Train Accuracy: 0.7857, Val Loss: 1.2081, Val Accuracy: 0.7009
Epoch 5896/10000, Train Loss: 1.1290, Train Accuracy: 0.7879, Val Loss: 1.2080, Val Accuracy: 0.7009
Epoch 5897/10000, Train Loss: 1.1402, Train Accuracy: 0.7757, Val Loss: 1.2078, Val Accuracy: 0.7009
Epoch 5898/10000, Train Loss: 1.1359, Train Accuracy: 0.7779, Val Loss: 1.2077, Val Accuracy: 0.7009
Epoch 5899/10000, Train Loss: 1.1252, Train Accuracy: 0.7902, Val Loss: 1.2077, Val Accuracy: 0.7009
Epoch 5900/10000, Train Loss: 1.1154, Train Accuracy: 0.8103, Val Loss: 1.2079, Val Accuracy: 0.7009
Epoch 5901/10000, Train Loss: 1.1350, Train Accuracy: 0.7812, Val Loss: 1.2077, Val Accuracy: 0.7009
Epoch 5902/10000, Train Loss: 1.1390, Train Accuracy: 0.7746, Val Loss: 1.2079, Val Accuracy: 0.7054
Epoch 5903/10000, Train Loss: 1.1165, Train Accuracy: 0.8002, Val Loss: 1.2078, Val Accuracy: 0.7054
Epoch 5904/10000, Train Loss: 1.1309, Train Accuracy: 0.7868, Val Loss: 1.2078, Val Accuracy: 0.7054
Epoch 5905/10000, Train Loss: 1.1223, Train Accuracy: 0.7924, Val Loss: 1.2079, Val Accuracy: 0.7054
Epoch 5906/10000, Train Loss: 1.1209, Train Accuracy: 0.7958, Val Loss: 1.2079, Val Accuracy: 0.7054
Epoch 5907/10000, Train Loss: 1.1290, Train Accuracy: 0.7812, Val Loss: 1.2078, Val Accuracy: 0.7054
Epoch 5908/10000, Train Loss: 1.1227, Train Accuracy: 0.7891, Val Loss: 1.2077, Val Accuracy: 0.7054
Epoch 5909/10000, Train Loss: 1.1233, Train Accuracy: 0.7835, Val Loss: 1.2081, Val Accuracy: 0.7009
Epoch 5910/10000, Train Loss: 1.1292, Train Accuracy: 0.7868, Val Loss: 1.2083, Val Accuracy: 0.7009
Epoch 5911/10000, Train Loss: 1.1190, Train Accuracy: 0.7935, Val Loss: 1.2081, Val Accuracy: 0.7009
Epoch 5912/10000, Train Loss: 1.1298, Train Accuracy: 0.7857, Val Loss: 1.2078, Val Accuracy: 0.7009
Epoch 5913/10000, Train Loss: 1.1231, Train Accuracy: 0.7980, Val Loss: 1.2075, Val Accuracy: 0.7009
Epoch 5914/10000, Train Loss: 1.1179, Train Accuracy: 0.8013, Val Loss: 1.2073, Val Accuracy: 0.7009
Epoch 5915/10000, Train Loss: 1.1174, Train Accuracy: 0.8025, Val Loss: 1.2070, Val Accuracy: 0.7009
Epoch 5916/10000, Train Loss: 1.1165, Train Accuracy: 0.8013, Val Loss: 1.2072, Val Accuracy: 0.7009
Epoch 5917/10000, Train Loss: 1.1265, Train Accuracy: 0.7902, Val Loss: 1.2073, Val Accuracy: 0.7009
Epoch 5918/10000, Train Loss: 1.1171, Train Accuracy: 0.8002, Val Loss: 1.2076, Val Accuracy: 0.7054
Epoch 5919/10000, Train Loss: 1.1239, Train Accuracy: 0.7868, Val Loss: 1.2076, Val Accuracy: 0.7009
Epoch 5920/10000, Train Loss: 1.1276, Train Accuracy: 0.7801, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5921/10000, Train Loss: 1.1327, Train Accuracy: 0.7902, Val Loss: 1.2082, Val Accuracy: 0.7009
Epoch 5922/10000, Train Loss: 1.1173, Train Accuracy: 0.8025, Val Loss: 1.2080, Val Accuracy: 0.7009
Epoch 5923/10000, Train Loss: 1.1256, Train Accuracy: 0.7902, Val Loss: 1.2078, Val Accuracy: 0.7009
Epoch 5924/10000, Train Loss: 1.1240, Train Accuracy: 0.7935, Val Loss: 1.2079, Val Accuracy: 0.7054
Epoch 5925/10000, Train Loss: 1.1209, Train Accuracy: 0.8002, Val Loss: 1.2077, Val Accuracy: 0.7054
Epoch 5926/10000, Train Loss: 1.1182, Train Accuracy: 0.7991, Val Loss: 1.2077, Val Accuracy: 0.7054
Epoch 5927/10000, Train Loss: 1.1263, Train Accuracy: 0.7924, Val Loss: 1.2076, Val Accuracy: 0.7054
Epoch 5928/10000, Train Loss: 1.1266, Train Accuracy: 0.7902, Val Loss: 1.2071, Val Accuracy: 0.7054
Epoch 5929/10000, Train Loss: 1.1275, Train Accuracy: 0.7935, Val Loss: 1.2071, Val Accuracy: 0.7054
Epoch 5930/10000, Train Loss: 1.1295, Train Accuracy: 0.7779, Val Loss: 1.2070, Val Accuracy: 0.7054
Epoch 5931/10000, Train Loss: 1.1128, Train Accuracy: 0.8036, Val Loss: 1.2069, Val Accuracy: 0.7009
Epoch 5932/10000, Train Loss: 1.1217, Train Accuracy: 0.7857, Val Loss: 1.2067, Val Accuracy: 0.7009
Epoch 5933/10000, Train Loss: 1.1120, Train Accuracy: 0.8047, Val Loss: 1.2065, Val Accuracy: 0.7009
Epoch 5934/10000, Train Loss: 1.1245, Train Accuracy: 0.7879, Val Loss: 1.2067, Val Accuracy: 0.7054
Epoch 5935/10000, Train Loss: 1.1276, Train Accuracy: 0.7902, Val Loss: 1.2067, Val Accuracy: 0.7054
Epoch 5936/10000, Train Loss: 1.1305, Train Accuracy: 0.7801, Val Loss: 1.2070, Val Accuracy: 0.7009
Epoch 5937/10000, Train Loss: 1.1157, Train Accuracy: 0.7980, Val Loss: 1.2071, Val Accuracy: 0.7009
Epoch 5938/10000, Train Loss: 1.1287, Train Accuracy: 0.7924, Val Loss: 1.2071, Val Accuracy: 0.7009
Epoch 5939/10000, Train Loss: 1.1138, Train Accuracy: 0.8013, Val Loss: 1.2069, Val Accuracy: 0.7009
Epoch 5940/10000, Train Loss: 1.1233, Train Accuracy: 0.7902, Val Loss: 1.2071, Val Accuracy: 0.7009
Epoch 5941/10000, Train Loss: 1.1115, Train Accuracy: 0.8103, Val Loss: 1.2069, Val Accuracy: 0.7009
Epoch 5942/10000, Train Loss: 1.1200, Train Accuracy: 0.8013, Val Loss: 1.2071, Val Accuracy: 0.7009
Epoch 5943/10000, Train Loss: 1.1225, Train Accuracy: 0.7891, Val Loss: 1.2071, Val Accuracy: 0.7009
Epoch 5944/10000, Train Loss: 1.1372, Train Accuracy: 0.7790, Val Loss: 1.2069, Val Accuracy: 0.7009
Epoch 5945/10000, Train Loss: 1.1204, Train Accuracy: 0.7946, Val Loss: 1.2070, Val Accuracy: 0.7009
Epoch 5946/10000, Train Loss: 1.1139, Train Accuracy: 0.8002, Val Loss: 1.2067, Val Accuracy: 0.7009
Epoch 5947/10000, Train Loss: 1.1235, Train Accuracy: 0.7935, Val Loss: 1.2065, Val Accuracy: 0.7054
Epoch 5948/10000, Train Loss: 1.1096, Train Accuracy: 0.7969, Val Loss: 1.2064, Val Accuracy: 0.7054
Epoch 5949/10000, Train Loss: 1.1281, Train Accuracy: 0.7879, Val Loss: 1.2062, Val Accuracy: 0.7054
Epoch 5950/10000, Train Loss: 1.1287, Train Accuracy: 0.7879, Val Loss: 1.2059, Val Accuracy: 0.7009
Epoch 5951/10000, Train Loss: 1.1273, Train Accuracy: 0.7857, Val Loss: 1.2061, Val Accuracy: 0.7009
Epoch 5952/10000, Train Loss: 1.1235, Train Accuracy: 0.7902, Val Loss: 1.2059, Val Accuracy: 0.7009
Epoch 5953/10000, Train Loss: 1.1290, Train Accuracy: 0.7812, Val Loss: 1.2060, Val Accuracy: 0.7009
Epoch 5954/10000, Train Loss: 1.1222, Train Accuracy: 0.7958, Val Loss: 1.2058, Val Accuracy: 0.7009
Epoch 5955/10000, Train Loss: 1.1196, Train Accuracy: 0.8025, Val Loss: 1.2058, Val Accuracy: 0.7009
Epoch 5956/10000, Train Loss: 1.1218, Train Accuracy: 0.7935, Val Loss: 1.2058, Val Accuracy: 0.7009
Epoch 5957/10000, Train Loss: 1.1258, Train Accuracy: 0.7846, Val Loss: 1.2057, Val Accuracy: 0.7009
Epoch 5958/10000, Train Loss: 1.1240, Train Accuracy: 0.7891, Val Loss: 1.2059, Val Accuracy: 0.7009
Epoch 5959/10000, Train Loss: 1.1329, Train Accuracy: 0.7857, Val Loss: 1.2058, Val Accuracy: 0.7054
Epoch 5960/10000, Train Loss: 1.1283, Train Accuracy: 0.7835, Val Loss: 1.2057, Val Accuracy: 0.7009
Epoch 5961/10000, Train Loss: 1.1265, Train Accuracy: 0.7902, Val Loss: 1.2057, Val Accuracy: 0.7054
Epoch 5962/10000, Train Loss: 1.1192, Train Accuracy: 0.7946, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 5963/10000, Train Loss: 1.1237, Train Accuracy: 0.7902, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 5964/10000, Train Loss: 1.1160, Train Accuracy: 0.7958, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 5965/10000, Train Loss: 1.1191, Train Accuracy: 0.7891, Val Loss: 1.2057, Val Accuracy: 0.7054
Epoch 5966/10000, Train Loss: 1.1226, Train Accuracy: 0.7958, Val Loss: 1.2058, Val Accuracy: 0.7054
Epoch 5967/10000, Train Loss: 1.1202, Train Accuracy: 0.7946, Val Loss: 1.2055, Val Accuracy: 0.7054
Epoch 5968/10000, Train Loss: 1.1179, Train Accuracy: 0.7980, Val Loss: 1.2055, Val Accuracy: 0.7054
Epoch 5969/10000, Train Loss: 1.1284, Train Accuracy: 0.7913, Val Loss: 1.2051, Val Accuracy: 0.7054
Epoch 5970/10000, Train Loss: 1.1194, Train Accuracy: 0.7924, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 5971/10000, Train Loss: 1.1121, Train Accuracy: 0.7946, Val Loss: 1.2051, Val Accuracy: 0.7054
Epoch 5972/10000, Train Loss: 1.1207, Train Accuracy: 0.7935, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 5973/10000, Train Loss: 1.1232, Train Accuracy: 0.7857, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 5974/10000, Train Loss: 1.1261, Train Accuracy: 0.7879, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 5975/10000, Train Loss: 1.1270, Train Accuracy: 0.7868, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 5976/10000, Train Loss: 1.1309, Train Accuracy: 0.7891, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 5977/10000, Train Loss: 1.1244, Train Accuracy: 0.7913, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 5978/10000, Train Loss: 1.1256, Train Accuracy: 0.7846, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 5979/10000, Train Loss: 1.1361, Train Accuracy: 0.7746, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 5980/10000, Train Loss: 1.1223, Train Accuracy: 0.7924, Val Loss: 1.2050, Val Accuracy: 0.7054
Epoch 5981/10000, Train Loss: 1.1175, Train Accuracy: 0.7991, Val Loss: 1.2050, Val Accuracy: 0.7054
Epoch 5982/10000, Train Loss: 1.1253, Train Accuracy: 0.7913, Val Loss: 1.2051, Val Accuracy: 0.7054
Epoch 5983/10000, Train Loss: 1.1245, Train Accuracy: 0.7902, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 5984/10000, Train Loss: 1.1115, Train Accuracy: 0.8069, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 5985/10000, Train Loss: 1.1192, Train Accuracy: 0.7980, Val Loss: 1.2050, Val Accuracy: 0.7054
Epoch 5986/10000, Train Loss: 1.1300, Train Accuracy: 0.7801, Val Loss: 1.2047, Val Accuracy: 0.7054
Epoch 5987/10000, Train Loss: 1.1190, Train Accuracy: 0.7935, Val Loss: 1.2050, Val Accuracy: 0.7054
Epoch 5988/10000, Train Loss: 1.1126, Train Accuracy: 0.8036, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 5989/10000, Train Loss: 1.1149, Train Accuracy: 0.7980, Val Loss: 1.2052, Val Accuracy: 0.7098
Epoch 5990/10000, Train Loss: 1.1207, Train Accuracy: 0.7891, Val Loss: 1.2050, Val Accuracy: 0.7054
Epoch 5991/10000, Train Loss: 1.1269, Train Accuracy: 0.7902, Val Loss: 1.2052, Val Accuracy: 0.7098
Epoch 5992/10000, Train Loss: 1.1270, Train Accuracy: 0.7879, Val Loss: 1.2051, Val Accuracy: 0.7098
Epoch 5993/10000, Train Loss: 1.1426, Train Accuracy: 0.7690, Val Loss: 1.2050, Val Accuracy: 0.7098
Epoch 5994/10000, Train Loss: 1.1203, Train Accuracy: 0.7958, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 5995/10000, Train Loss: 1.1198, Train Accuracy: 0.7980, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 5996/10000, Train Loss: 1.1295, Train Accuracy: 0.7812, Val Loss: 1.2051, Val Accuracy: 0.7098
Epoch 5997/10000, Train Loss: 1.1075, Train Accuracy: 0.8080, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 5998/10000, Train Loss: 1.1050, Train Accuracy: 0.8125, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 5999/10000, Train Loss: 1.1299, Train Accuracy: 0.7835, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 6000/10000, Train Loss: 1.1231, Train Accuracy: 0.7924, Val Loss: 1.2046, Val Accuracy: 0.7098
Epoch 6001/10000, Train Loss: 1.1130, Train Accuracy: 0.8047, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 6002/10000, Train Loss: 1.1126, Train Accuracy: 0.8069, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 6003/10000, Train Loss: 1.1112, Train Accuracy: 0.8080, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 6004/10000, Train Loss: 1.1176, Train Accuracy: 0.7891, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 6005/10000, Train Loss: 1.1201, Train Accuracy: 0.7946, Val Loss: 1.2047, Val Accuracy: 0.7098
Epoch 6006/10000, Train Loss: 1.1058, Train Accuracy: 0.8136, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 6007/10000, Train Loss: 1.1117, Train Accuracy: 0.8013, Val Loss: 1.2048, Val Accuracy: 0.7098
Epoch 6008/10000, Train Loss: 1.1316, Train Accuracy: 0.7857, Val Loss: 1.2048, Val Accuracy: 0.7098
Epoch 6009/10000, Train Loss: 1.1081, Train Accuracy: 0.8136, Val Loss: 1.2048, Val Accuracy: 0.7098
Epoch 6010/10000, Train Loss: 1.1245, Train Accuracy: 0.7857, Val Loss: 1.2046, Val Accuracy: 0.7098
Epoch 6011/10000, Train Loss: 1.1223, Train Accuracy: 0.8002, Val Loss: 1.2050, Val Accuracy: 0.7098
Epoch 6012/10000, Train Loss: 1.1132, Train Accuracy: 0.8092, Val Loss: 1.2048, Val Accuracy: 0.7098
Epoch 6013/10000, Train Loss: 1.1075, Train Accuracy: 0.8069, Val Loss: 1.2051, Val Accuracy: 0.7098
Epoch 6014/10000, Train Loss: 1.1344, Train Accuracy: 0.7768, Val Loss: 1.2054, Val Accuracy: 0.7098
Epoch 6015/10000, Train Loss: 1.1266, Train Accuracy: 0.7868, Val Loss: 1.2054, Val Accuracy: 0.7098
Epoch 6016/10000, Train Loss: 1.1132, Train Accuracy: 0.8114, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 6017/10000, Train Loss: 1.1316, Train Accuracy: 0.7824, Val Loss: 1.2055, Val Accuracy: 0.7054
Epoch 6018/10000, Train Loss: 1.1156, Train Accuracy: 0.7991, Val Loss: 1.2055, Val Accuracy: 0.7009
Epoch 6019/10000, Train Loss: 1.1129, Train Accuracy: 0.8080, Val Loss: 1.2056, Val Accuracy: 0.7009
Epoch 6020/10000, Train Loss: 1.1268, Train Accuracy: 0.7801, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 6021/10000, Train Loss: 1.1216, Train Accuracy: 0.7891, Val Loss: 1.2055, Val Accuracy: 0.7054
Epoch 6022/10000, Train Loss: 1.1082, Train Accuracy: 0.8114, Val Loss: 1.2057, Val Accuracy: 0.6964
Epoch 6023/10000, Train Loss: 1.1214, Train Accuracy: 0.7946, Val Loss: 1.2052, Val Accuracy: 0.7009
Epoch 6024/10000, Train Loss: 1.1274, Train Accuracy: 0.7879, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 6025/10000, Train Loss: 1.1228, Train Accuracy: 0.7857, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 6026/10000, Train Loss: 1.1206, Train Accuracy: 0.7946, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 6027/10000, Train Loss: 1.1167, Train Accuracy: 0.8036, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 6028/10000, Train Loss: 1.1304, Train Accuracy: 0.7790, Val Loss: 1.2056, Val Accuracy: 0.7054
Epoch 6029/10000, Train Loss: 1.1222, Train Accuracy: 0.7879, Val Loss: 1.2058, Val Accuracy: 0.7009
Epoch 6030/10000, Train Loss: 1.1166, Train Accuracy: 0.8069, Val Loss: 1.2055, Val Accuracy: 0.7009
Epoch 6031/10000, Train Loss: 1.1294, Train Accuracy: 0.7846, Val Loss: 1.2056, Val Accuracy: 0.7009
Epoch 6032/10000, Train Loss: 1.1129, Train Accuracy: 0.8025, Val Loss: 1.2056, Val Accuracy: 0.7054
Epoch 6033/10000, Train Loss: 1.1237, Train Accuracy: 0.7790, Val Loss: 1.2057, Val Accuracy: 0.7009
Epoch 6034/10000, Train Loss: 1.1176, Train Accuracy: 0.7902, Val Loss: 1.2057, Val Accuracy: 0.7054
Epoch 6035/10000, Train Loss: 1.1149, Train Accuracy: 0.7958, Val Loss: 1.2055, Val Accuracy: 0.7054
Epoch 6036/10000, Train Loss: 1.1224, Train Accuracy: 0.7868, Val Loss: 1.2054, Val Accuracy: 0.7054
Epoch 6037/10000, Train Loss: 1.1155, Train Accuracy: 0.8058, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 6038/10000, Train Loss: 1.1109, Train Accuracy: 0.8092, Val Loss: 1.2053, Val Accuracy: 0.7054
Epoch 6039/10000, Train Loss: 1.1188, Train Accuracy: 0.8025, Val Loss: 1.2051, Val Accuracy: 0.7054
Epoch 6040/10000, Train Loss: 1.1082, Train Accuracy: 0.8181, Val Loss: 1.2048, Val Accuracy: 0.7054
Epoch 6041/10000, Train Loss: 1.1199, Train Accuracy: 0.7991, Val Loss: 1.2050, Val Accuracy: 0.7009
Epoch 6042/10000, Train Loss: 1.1155, Train Accuracy: 0.7969, Val Loss: 1.2051, Val Accuracy: 0.7009
Epoch 6043/10000, Train Loss: 1.1104, Train Accuracy: 0.8114, Val Loss: 1.2052, Val Accuracy: 0.7054
Epoch 6044/10000, Train Loss: 1.1259, Train Accuracy: 0.7879, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 6045/10000, Train Loss: 1.1221, Train Accuracy: 0.7935, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 6046/10000, Train Loss: 1.1079, Train Accuracy: 0.8170, Val Loss: 1.2049, Val Accuracy: 0.7098
Epoch 6047/10000, Train Loss: 1.1141, Train Accuracy: 0.8025, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 6048/10000, Train Loss: 1.1155, Train Accuracy: 0.8002, Val Loss: 1.2049, Val Accuracy: 0.7054
Epoch 6049/10000, Train Loss: 1.1306, Train Accuracy: 0.7779, Val Loss: 1.2050, Val Accuracy: 0.7009
Epoch 6050/10000, Train Loss: 1.1190, Train Accuracy: 0.7913, Val Loss: 1.2048, Val Accuracy: 0.7009
Epoch 6051/10000, Train Loss: 1.1152, Train Accuracy: 0.8058, Val Loss: 1.2049, Val Accuracy: 0.7009
Epoch 6052/10000, Train Loss: 1.1135, Train Accuracy: 0.8013, Val Loss: 1.2049, Val Accuracy: 0.7009
Epoch 6053/10000, Train Loss: 1.1275, Train Accuracy: 0.7846, Val Loss: 1.2047, Val Accuracy: 0.7054
Epoch 6054/10000, Train Loss: 1.1214, Train Accuracy: 0.7935, Val Loss: 1.2047, Val Accuracy: 0.7009
Epoch 6055/10000, Train Loss: 1.1248, Train Accuracy: 0.7879, Val Loss: 1.2046, Val Accuracy: 0.7054
Epoch 6056/10000, Train Loss: 1.1104, Train Accuracy: 0.8092, Val Loss: 1.2046, Val Accuracy: 0.7054
Epoch 6057/10000, Train Loss: 1.1100, Train Accuracy: 0.8158, Val Loss: 1.2043, Val Accuracy: 0.7143
Epoch 6058/10000, Train Loss: 1.1202, Train Accuracy: 0.7902, Val Loss: 1.2045, Val Accuracy: 0.7098
Epoch 6059/10000, Train Loss: 1.1208, Train Accuracy: 0.7913, Val Loss: 1.2045, Val Accuracy: 0.7098
Epoch 6060/10000, Train Loss: 1.1247, Train Accuracy: 0.7913, Val Loss: 1.2044, Val Accuracy: 0.7054
Epoch 6061/10000, Train Loss: 1.1107, Train Accuracy: 0.8103, Val Loss: 1.2043, Val Accuracy: 0.7054
Epoch 6062/10000, Train Loss: 1.1166, Train Accuracy: 0.8002, Val Loss: 1.2042, Val Accuracy: 0.7054
Epoch 6063/10000, Train Loss: 1.1037, Train Accuracy: 0.8170, Val Loss: 1.2042, Val Accuracy: 0.7054
Epoch 6064/10000, Train Loss: 1.1085, Train Accuracy: 0.8147, Val Loss: 1.2043, Val Accuracy: 0.7054
Epoch 6065/10000, Train Loss: 1.1211, Train Accuracy: 0.8002, Val Loss: 1.2042, Val Accuracy: 0.7054
Epoch 6066/10000, Train Loss: 1.1285, Train Accuracy: 0.7768, Val Loss: 1.2043, Val Accuracy: 0.7054
Epoch 6067/10000, Train Loss: 1.1169, Train Accuracy: 0.7924, Val Loss: 1.2042, Val Accuracy: 0.7054
Epoch 6068/10000, Train Loss: 1.1148, Train Accuracy: 0.7946, Val Loss: 1.2041, Val Accuracy: 0.7054
Epoch 6069/10000, Train Loss: 1.1178, Train Accuracy: 0.8002, Val Loss: 1.2044, Val Accuracy: 0.7054
Epoch 6070/10000, Train Loss: 1.1177, Train Accuracy: 0.7969, Val Loss: 1.2049, Val Accuracy: 0.7009
Epoch 6071/10000, Train Loss: 1.1167, Train Accuracy: 0.8047, Val Loss: 1.2050, Val Accuracy: 0.6964
Epoch 6072/10000, Train Loss: 1.1139, Train Accuracy: 0.8047, Val Loss: 1.2048, Val Accuracy: 0.7009
Epoch 6073/10000, Train Loss: 1.1227, Train Accuracy: 0.7924, Val Loss: 1.2047, Val Accuracy: 0.7009
Epoch 6074/10000, Train Loss: 1.1341, Train Accuracy: 0.7757, Val Loss: 1.2047, Val Accuracy: 0.7054
Epoch 6075/10000, Train Loss: 1.1182, Train Accuracy: 0.8013, Val Loss: 1.2044, Val Accuracy: 0.7054
Epoch 6076/10000, Train Loss: 1.1096, Train Accuracy: 0.8036, Val Loss: 1.2045, Val Accuracy: 0.7054
Epoch 6077/10000, Train Loss: 1.1227, Train Accuracy: 0.7958, Val Loss: 1.2044, Val Accuracy: 0.7054
Epoch 6078/10000, Train Loss: 1.1176, Train Accuracy: 0.8080, Val Loss: 1.2041, Val Accuracy: 0.7054
Epoch 6079/10000, Train Loss: 1.1201, Train Accuracy: 0.7879, Val Loss: 1.2040, Val Accuracy: 0.7098
Epoch 6080/10000, Train Loss: 1.1171, Train Accuracy: 0.8025, Val Loss: 1.2039, Val Accuracy: 0.7098
Epoch 6081/10000, Train Loss: 1.1163, Train Accuracy: 0.8036, Val Loss: 1.2036, Val Accuracy: 0.7054
Epoch 6082/10000, Train Loss: 1.1147, Train Accuracy: 0.7924, Val Loss: 1.2033, Val Accuracy: 0.7098
Epoch 6083/10000, Train Loss: 1.1227, Train Accuracy: 0.7935, Val Loss: 1.2031, Val Accuracy: 0.7054
Epoch 6084/10000, Train Loss: 1.1220, Train Accuracy: 0.7935, Val Loss: 1.2031, Val Accuracy: 0.7098
Epoch 6085/10000, Train Loss: 1.1121, Train Accuracy: 0.8058, Val Loss: 1.2032, Val Accuracy: 0.7054
Epoch 6086/10000, Train Loss: 1.1169, Train Accuracy: 0.7913, Val Loss: 1.2029, Val Accuracy: 0.7054
Epoch 6087/10000, Train Loss: 1.1155, Train Accuracy: 0.8025, Val Loss: 1.2029, Val Accuracy: 0.7098
Epoch 6088/10000, Train Loss: 1.1214, Train Accuracy: 0.7991, Val Loss: 1.2031, Val Accuracy: 0.7098
Epoch 6089/10000, Train Loss: 1.1148, Train Accuracy: 0.7946, Val Loss: 1.2032, Val Accuracy: 0.7054
Epoch 6090/10000, Train Loss: 1.1091, Train Accuracy: 0.8147, Val Loss: 1.2034, Val Accuracy: 0.7054
Epoch 6091/10000, Train Loss: 1.1234, Train Accuracy: 0.7946, Val Loss: 1.2035, Val Accuracy: 0.7009
Epoch 6092/10000, Train Loss: 1.1207, Train Accuracy: 0.7946, Val Loss: 1.2033, Val Accuracy: 0.7054
Epoch 6093/10000, Train Loss: 1.1140, Train Accuracy: 0.8092, Val Loss: 1.2033, Val Accuracy: 0.7143
Epoch 6094/10000, Train Loss: 1.1311, Train Accuracy: 0.7824, Val Loss: 1.2034, Val Accuracy: 0.7098
Epoch 6095/10000, Train Loss: 1.1165, Train Accuracy: 0.8047, Val Loss: 1.2036, Val Accuracy: 0.7054
Epoch 6096/10000, Train Loss: 1.1193, Train Accuracy: 0.8013, Val Loss: 1.2033, Val Accuracy: 0.7054
Epoch 6097/10000, Train Loss: 1.1350, Train Accuracy: 0.7801, Val Loss: 1.2034, Val Accuracy: 0.7054
Epoch 6098/10000, Train Loss: 1.1161, Train Accuracy: 0.7879, Val Loss: 1.2031, Val Accuracy: 0.7054
Epoch 6099/10000, Train Loss: 1.1048, Train Accuracy: 0.8058, Val Loss: 1.2032, Val Accuracy: 0.7054
Epoch 6100/10000, Train Loss: 1.1226, Train Accuracy: 0.7913, Val Loss: 1.2031, Val Accuracy: 0.7054
Epoch 6101/10000, Train Loss: 1.1181, Train Accuracy: 0.8013, Val Loss: 1.2031, Val Accuracy: 0.7098
Epoch 6102/10000, Train Loss: 1.1266, Train Accuracy: 0.7812, Val Loss: 1.2031, Val Accuracy: 0.7054
Epoch 6103/10000, Train Loss: 1.0969, Train Accuracy: 0.8170, Val Loss: 1.2031, Val Accuracy: 0.7009
Epoch 6104/10000, Train Loss: 1.1197, Train Accuracy: 0.7913, Val Loss: 1.2030, Val Accuracy: 0.7009
Epoch 6105/10000, Train Loss: 1.1065, Train Accuracy: 0.8103, Val Loss: 1.2026, Val Accuracy: 0.7054
Epoch 6106/10000, Train Loss: 1.1121, Train Accuracy: 0.7958, Val Loss: 1.2025, Val Accuracy: 0.7098
Epoch 6107/10000, Train Loss: 1.1089, Train Accuracy: 0.8025, Val Loss: 1.2023, Val Accuracy: 0.7054
Epoch 6108/10000, Train Loss: 1.1247, Train Accuracy: 0.7835, Val Loss: 1.2024, Val Accuracy: 0.7054
Epoch 6109/10000, Train Loss: 1.1013, Train Accuracy: 0.8214, Val Loss: 1.2021, Val Accuracy: 0.7054
Epoch 6110/10000, Train Loss: 1.1248, Train Accuracy: 0.7935, Val Loss: 1.2022, Val Accuracy: 0.7054
Epoch 6111/10000, Train Loss: 1.1231, Train Accuracy: 0.7891, Val Loss: 1.2021, Val Accuracy: 0.7054
Epoch 6112/10000, Train Loss: 1.1207, Train Accuracy: 0.7913, Val Loss: 1.2020, Val Accuracy: 0.7054
Epoch 6113/10000, Train Loss: 1.1162, Train Accuracy: 0.7969, Val Loss: 1.2021, Val Accuracy: 0.7054
Epoch 6114/10000, Train Loss: 1.1180, Train Accuracy: 0.7969, Val Loss: 1.2022, Val Accuracy: 0.7054
Epoch 6115/10000, Train Loss: 1.1172, Train Accuracy: 0.7969, Val Loss: 1.2023, Val Accuracy: 0.7098
Epoch 6116/10000, Train Loss: 1.1032, Train Accuracy: 0.8203, Val Loss: 1.2023, Val Accuracy: 0.7143
Epoch 6117/10000, Train Loss: 1.1204, Train Accuracy: 0.7935, Val Loss: 1.2018, Val Accuracy: 0.7143
Epoch 6118/10000, Train Loss: 1.1125, Train Accuracy: 0.8080, Val Loss: 1.2019, Val Accuracy: 0.7143
Epoch 6119/10000, Train Loss: 1.1145, Train Accuracy: 0.8047, Val Loss: 1.2020, Val Accuracy: 0.7143
Epoch 6120/10000, Train Loss: 1.1087, Train Accuracy: 0.8036, Val Loss: 1.2019, Val Accuracy: 0.7098
Epoch 6121/10000, Train Loss: 1.1204, Train Accuracy: 0.7980, Val Loss: 1.2018, Val Accuracy: 0.7143
Epoch 6122/10000, Train Loss: 1.1093, Train Accuracy: 0.8047, Val Loss: 1.2017, Val Accuracy: 0.7143
Epoch 6123/10000, Train Loss: 1.1203, Train Accuracy: 0.7891, Val Loss: 1.2016, Val Accuracy: 0.7143
Epoch 6124/10000, Train Loss: 1.1246, Train Accuracy: 0.7879, Val Loss: 1.2015, Val Accuracy: 0.7143
Epoch 6125/10000, Train Loss: 1.1214, Train Accuracy: 0.7857, Val Loss: 1.2013, Val Accuracy: 0.7143
Epoch 6126/10000, Train Loss: 1.1152, Train Accuracy: 0.7969, Val Loss: 1.2013, Val Accuracy: 0.7143
Epoch 6127/10000, Train Loss: 1.1251, Train Accuracy: 0.7902, Val Loss: 1.2012, Val Accuracy: 0.7143
Epoch 6128/10000, Train Loss: 1.1163, Train Accuracy: 0.7969, Val Loss: 1.2010, Val Accuracy: 0.7143
Epoch 6129/10000, Train Loss: 1.1422, Train Accuracy: 0.7645, Val Loss: 1.2012, Val Accuracy: 0.7143
Epoch 6130/10000, Train Loss: 1.1139, Train Accuracy: 0.8013, Val Loss: 1.2011, Val Accuracy: 0.7143
Epoch 6131/10000, Train Loss: 1.1238, Train Accuracy: 0.7913, Val Loss: 1.2012, Val Accuracy: 0.7143
Epoch 6132/10000, Train Loss: 1.1269, Train Accuracy: 0.7812, Val Loss: 1.2013, Val Accuracy: 0.7143
Epoch 6133/10000, Train Loss: 1.1190, Train Accuracy: 0.7980, Val Loss: 1.2012, Val Accuracy: 0.7143
Epoch 6134/10000, Train Loss: 1.1076, Train Accuracy: 0.8080, Val Loss: 1.2014, Val Accuracy: 0.7143
Epoch 6135/10000, Train Loss: 1.1323, Train Accuracy: 0.7846, Val Loss: 1.2013, Val Accuracy: 0.7143
Epoch 6136/10000, Train Loss: 1.1225, Train Accuracy: 0.7835, Val Loss: 1.2013, Val Accuracy: 0.7143
Epoch 6137/10000, Train Loss: 1.1129, Train Accuracy: 0.8080, Val Loss: 1.2010, Val Accuracy: 0.7143
Epoch 6138/10000, Train Loss: 1.1023, Train Accuracy: 0.8114, Val Loss: 1.2008, Val Accuracy: 0.7143
Epoch 6139/10000, Train Loss: 1.1055, Train Accuracy: 0.8192, Val Loss: 1.2004, Val Accuracy: 0.7143
Epoch 6140/10000, Train Loss: 1.1166, Train Accuracy: 0.7980, Val Loss: 1.2003, Val Accuracy: 0.7098
Epoch 6141/10000, Train Loss: 1.1245, Train Accuracy: 0.7946, Val Loss: 1.2005, Val Accuracy: 0.7098
Epoch 6142/10000, Train Loss: 1.1254, Train Accuracy: 0.7868, Val Loss: 1.2003, Val Accuracy: 0.7054
Epoch 6143/10000, Train Loss: 1.1312, Train Accuracy: 0.7812, Val Loss: 1.2003, Val Accuracy: 0.7054
Epoch 6144/10000, Train Loss: 1.1166, Train Accuracy: 0.8002, Val Loss: 1.2002, Val Accuracy: 0.7098
Epoch 6145/10000, Train Loss: 1.1232, Train Accuracy: 0.7812, Val Loss: 1.2002, Val Accuracy: 0.7143
Epoch 6146/10000, Train Loss: 1.1148, Train Accuracy: 0.8036, Val Loss: 1.2001, Val Accuracy: 0.7143
Epoch 6147/10000, Train Loss: 1.1101, Train Accuracy: 0.8092, Val Loss: 1.1998, Val Accuracy: 0.7098
Epoch 6148/10000, Train Loss: 1.1161, Train Accuracy: 0.7980, Val Loss: 1.1999, Val Accuracy: 0.7098
Epoch 6149/10000, Train Loss: 1.1074, Train Accuracy: 0.8080, Val Loss: 1.1997, Val Accuracy: 0.7098
Epoch 6150/10000, Train Loss: 1.1079, Train Accuracy: 0.8125, Val Loss: 1.1996, Val Accuracy: 0.7098
Epoch 6151/10000, Train Loss: 1.1131, Train Accuracy: 0.8047, Val Loss: 1.1997, Val Accuracy: 0.7098
Epoch 6152/10000, Train Loss: 1.1103, Train Accuracy: 0.8069, Val Loss: 1.1996, Val Accuracy: 0.7098
Epoch 6153/10000, Train Loss: 1.1217, Train Accuracy: 0.7812, Val Loss: 1.1999, Val Accuracy: 0.7098
Epoch 6154/10000, Train Loss: 1.1223, Train Accuracy: 0.7891, Val Loss: 1.2001, Val Accuracy: 0.7098
Epoch 6155/10000, Train Loss: 1.1164, Train Accuracy: 0.8047, Val Loss: 1.2002, Val Accuracy: 0.7098
Epoch 6156/10000, Train Loss: 1.1190, Train Accuracy: 0.7924, Val Loss: 1.2001, Val Accuracy: 0.7098
Epoch 6157/10000, Train Loss: 1.1137, Train Accuracy: 0.8002, Val Loss: 1.1999, Val Accuracy: 0.7098
Epoch 6158/10000, Train Loss: 1.1170, Train Accuracy: 0.7980, Val Loss: 1.1996, Val Accuracy: 0.7143
Epoch 6159/10000, Train Loss: 1.1145, Train Accuracy: 0.8092, Val Loss: 1.1995, Val Accuracy: 0.7188
Epoch 6160/10000, Train Loss: 1.1209, Train Accuracy: 0.7935, Val Loss: 1.1995, Val Accuracy: 0.7188
Epoch 6161/10000, Train Loss: 1.1167, Train Accuracy: 0.8047, Val Loss: 1.1993, Val Accuracy: 0.7188
Epoch 6162/10000, Train Loss: 1.1128, Train Accuracy: 0.8047, Val Loss: 1.1995, Val Accuracy: 0.7143
Epoch 6163/10000, Train Loss: 1.1147, Train Accuracy: 0.7958, Val Loss: 1.1995, Val Accuracy: 0.7143
Epoch 6164/10000, Train Loss: 1.1162, Train Accuracy: 0.8013, Val Loss: 1.1993, Val Accuracy: 0.7143
Epoch 6165/10000, Train Loss: 1.1100, Train Accuracy: 0.8058, Val Loss: 1.1991, Val Accuracy: 0.7143
Epoch 6166/10000, Train Loss: 1.1143, Train Accuracy: 0.8013, Val Loss: 1.1992, Val Accuracy: 0.7143
Epoch 6167/10000, Train Loss: 1.1217, Train Accuracy: 0.7913, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6168/10000, Train Loss: 1.1180, Train Accuracy: 0.7958, Val Loss: 1.1992, Val Accuracy: 0.7143
Epoch 6169/10000, Train Loss: 1.1066, Train Accuracy: 0.8092, Val Loss: 1.1989, Val Accuracy: 0.7143
Epoch 6170/10000, Train Loss: 1.1197, Train Accuracy: 0.7980, Val Loss: 1.1989, Val Accuracy: 0.7143
Epoch 6171/10000, Train Loss: 1.1133, Train Accuracy: 0.7991, Val Loss: 1.1987, Val Accuracy: 0.7098
Epoch 6172/10000, Train Loss: 1.1152, Train Accuracy: 0.7924, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6173/10000, Train Loss: 1.1147, Train Accuracy: 0.7991, Val Loss: 1.1990, Val Accuracy: 0.7098
Epoch 6174/10000, Train Loss: 1.1006, Train Accuracy: 0.8170, Val Loss: 1.1993, Val Accuracy: 0.7098
Epoch 6175/10000, Train Loss: 1.1176, Train Accuracy: 0.7946, Val Loss: 1.1995, Val Accuracy: 0.7143
Epoch 6176/10000, Train Loss: 1.1167, Train Accuracy: 0.7969, Val Loss: 1.1992, Val Accuracy: 0.7188
Epoch 6177/10000, Train Loss: 1.1092, Train Accuracy: 0.8036, Val Loss: 1.1989, Val Accuracy: 0.7143
Epoch 6178/10000, Train Loss: 1.1096, Train Accuracy: 0.8092, Val Loss: 1.1991, Val Accuracy: 0.7143
Epoch 6179/10000, Train Loss: 1.1118, Train Accuracy: 0.8036, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6180/10000, Train Loss: 1.1154, Train Accuracy: 0.7980, Val Loss: 1.1990, Val Accuracy: 0.7188
Epoch 6181/10000, Train Loss: 1.1057, Train Accuracy: 0.8136, Val Loss: 1.1991, Val Accuracy: 0.7188
Epoch 6182/10000, Train Loss: 1.1180, Train Accuracy: 0.8047, Val Loss: 1.1991, Val Accuracy: 0.7188
Epoch 6183/10000, Train Loss: 1.1244, Train Accuracy: 0.7868, Val Loss: 1.1991, Val Accuracy: 0.7188
Epoch 6184/10000, Train Loss: 1.1150, Train Accuracy: 0.8058, Val Loss: 1.1993, Val Accuracy: 0.7143
Epoch 6185/10000, Train Loss: 1.1054, Train Accuracy: 0.8114, Val Loss: 1.1992, Val Accuracy: 0.7143
Epoch 6186/10000, Train Loss: 1.1177, Train Accuracy: 0.7958, Val Loss: 1.1990, Val Accuracy: 0.7188
Epoch 6187/10000, Train Loss: 1.1131, Train Accuracy: 0.8002, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6188/10000, Train Loss: 1.1133, Train Accuracy: 0.8002, Val Loss: 1.1990, Val Accuracy: 0.7188
Epoch 6189/10000, Train Loss: 1.1077, Train Accuracy: 0.8092, Val Loss: 1.1988, Val Accuracy: 0.7143
Epoch 6190/10000, Train Loss: 1.1102, Train Accuracy: 0.8013, Val Loss: 1.1989, Val Accuracy: 0.7188
Epoch 6191/10000, Train Loss: 1.1190, Train Accuracy: 0.7958, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6192/10000, Train Loss: 1.1152, Train Accuracy: 0.8092, Val Loss: 1.1988, Val Accuracy: 0.7098
Epoch 6193/10000, Train Loss: 1.1143, Train Accuracy: 0.7946, Val Loss: 1.1988, Val Accuracy: 0.7098
Epoch 6194/10000, Train Loss: 1.1203, Train Accuracy: 0.7946, Val Loss: 1.1990, Val Accuracy: 0.7054
Epoch 6195/10000, Train Loss: 1.1194, Train Accuracy: 0.7924, Val Loss: 1.1990, Val Accuracy: 0.7098
Epoch 6196/10000, Train Loss: 1.1240, Train Accuracy: 0.7913, Val Loss: 1.1988, Val Accuracy: 0.7098
Epoch 6197/10000, Train Loss: 1.1079, Train Accuracy: 0.8047, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6198/10000, Train Loss: 1.0991, Train Accuracy: 0.8136, Val Loss: 1.1991, Val Accuracy: 0.7098
Epoch 6199/10000, Train Loss: 1.1151, Train Accuracy: 0.7958, Val Loss: 1.1991, Val Accuracy: 0.7143
Epoch 6200/10000, Train Loss: 1.1164, Train Accuracy: 0.8013, Val Loss: 1.1988, Val Accuracy: 0.7143
Epoch 6201/10000, Train Loss: 1.1127, Train Accuracy: 0.8013, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6202/10000, Train Loss: 1.1055, Train Accuracy: 0.8103, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6203/10000, Train Loss: 1.1140, Train Accuracy: 0.8047, Val Loss: 1.1990, Val Accuracy: 0.7143
Epoch 6204/10000, Train Loss: 1.1120, Train Accuracy: 0.7935, Val Loss: 1.1995, Val Accuracy: 0.7143
Epoch 6205/10000, Train Loss: 1.1023, Train Accuracy: 0.8125, Val Loss: 1.1994, Val Accuracy: 0.7098
Epoch 6206/10000, Train Loss: 1.1186, Train Accuracy: 0.7991, Val Loss: 1.1994, Val Accuracy: 0.7054
Epoch 6207/10000, Train Loss: 1.1084, Train Accuracy: 0.8047, Val Loss: 1.1996, Val Accuracy: 0.7054
Epoch 6208/10000, Train Loss: 1.1037, Train Accuracy: 0.8069, Val Loss: 1.1995, Val Accuracy: 0.7098
Epoch 6209/10000, Train Loss: 1.1267, Train Accuracy: 0.7812, Val Loss: 1.1995, Val Accuracy: 0.7098
Epoch 6210/10000, Train Loss: 1.1144, Train Accuracy: 0.8069, Val Loss: 1.1997, Val Accuracy: 0.7098
Epoch 6211/10000, Train Loss: 1.1137, Train Accuracy: 0.7980, Val Loss: 1.1997, Val Accuracy: 0.7098
Epoch 6212/10000, Train Loss: 1.1119, Train Accuracy: 0.8047, Val Loss: 1.1998, Val Accuracy: 0.7098
Epoch 6213/10000, Train Loss: 1.1152, Train Accuracy: 0.7924, Val Loss: 1.1996, Val Accuracy: 0.7143
Epoch 6214/10000, Train Loss: 1.1068, Train Accuracy: 0.8047, Val Loss: 1.1996, Val Accuracy: 0.7143
Epoch 6215/10000, Train Loss: 1.1144, Train Accuracy: 0.8025, Val Loss: 1.1995, Val Accuracy: 0.7098
Epoch 6216/10000, Train Loss: 1.1174, Train Accuracy: 0.7958, Val Loss: 1.1995, Val Accuracy: 0.7098
Epoch 6217/10000, Train Loss: 1.1167, Train Accuracy: 0.7969, Val Loss: 1.1996, Val Accuracy: 0.7098
Epoch 6218/10000, Train Loss: 1.1148, Train Accuracy: 0.7980, Val Loss: 1.1998, Val Accuracy: 0.7143
Epoch 6219/10000, Train Loss: 1.1221, Train Accuracy: 0.7958, Val Loss: 1.1996, Val Accuracy: 0.7098
Epoch 6220/10000, Train Loss: 1.1183, Train Accuracy: 0.7857, Val Loss: 1.1993, Val Accuracy: 0.7098
Epoch 6221/10000, Train Loss: 1.1125, Train Accuracy: 0.7991, Val Loss: 1.1991, Val Accuracy: 0.7098
Epoch 6222/10000, Train Loss: 1.1138, Train Accuracy: 0.8036, Val Loss: 1.1990, Val Accuracy: 0.7098
Epoch 6223/10000, Train Loss: 1.1174, Train Accuracy: 0.8002, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6224/10000, Train Loss: 1.1191, Train Accuracy: 0.7958, Val Loss: 1.1987, Val Accuracy: 0.7098
Epoch 6225/10000, Train Loss: 1.1255, Train Accuracy: 0.7835, Val Loss: 1.1988, Val Accuracy: 0.7098
Epoch 6226/10000, Train Loss: 1.1117, Train Accuracy: 0.7969, Val Loss: 1.1987, Val Accuracy: 0.7098
Epoch 6227/10000, Train Loss: 1.1149, Train Accuracy: 0.8036, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6228/10000, Train Loss: 1.1100, Train Accuracy: 0.8013, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6229/10000, Train Loss: 1.1099, Train Accuracy: 0.8080, Val Loss: 1.1989, Val Accuracy: 0.7098
Epoch 6230/10000, Train Loss: 1.1144, Train Accuracy: 0.8036, Val Loss: 1.1986, Val Accuracy: 0.7098
Epoch 6231/10000, Train Loss: 1.1093, Train Accuracy: 0.8103, Val Loss: 1.1981, Val Accuracy: 0.7098
Epoch 6232/10000, Train Loss: 1.1077, Train Accuracy: 0.8069, Val Loss: 1.1982, Val Accuracy: 0.7098
Epoch 6233/10000, Train Loss: 1.1245, Train Accuracy: 0.7868, Val Loss: 1.1978, Val Accuracy: 0.7143
Epoch 6234/10000, Train Loss: 1.1078, Train Accuracy: 0.8047, Val Loss: 1.1982, Val Accuracy: 0.7143
Epoch 6235/10000, Train Loss: 1.1182, Train Accuracy: 0.7924, Val Loss: 1.1980, Val Accuracy: 0.7098
Epoch 6236/10000, Train Loss: 1.1054, Train Accuracy: 0.8114, Val Loss: 1.1982, Val Accuracy: 0.7143
Epoch 6237/10000, Train Loss: 1.1025, Train Accuracy: 0.8092, Val Loss: 1.1982, Val Accuracy: 0.7143
Epoch 6238/10000, Train Loss: 1.1287, Train Accuracy: 0.7779, Val Loss: 1.1980, Val Accuracy: 0.7098
Epoch 6239/10000, Train Loss: 1.1081, Train Accuracy: 0.8103, Val Loss: 1.1980, Val Accuracy: 0.7098
Epoch 6240/10000, Train Loss: 1.1008, Train Accuracy: 0.8080, Val Loss: 1.1978, Val Accuracy: 0.7098
Epoch 6241/10000, Train Loss: 1.1081, Train Accuracy: 0.8069, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6242/10000, Train Loss: 1.1117, Train Accuracy: 0.8036, Val Loss: 1.1978, Val Accuracy: 0.7098
Epoch 6243/10000, Train Loss: 1.1213, Train Accuracy: 0.7812, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6244/10000, Train Loss: 1.1041, Train Accuracy: 0.8136, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6245/10000, Train Loss: 1.1223, Train Accuracy: 0.7891, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6246/10000, Train Loss: 1.1074, Train Accuracy: 0.8047, Val Loss: 1.1978, Val Accuracy: 0.7098
Epoch 6247/10000, Train Loss: 1.1171, Train Accuracy: 0.7879, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6248/10000, Train Loss: 1.0991, Train Accuracy: 0.8158, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6249/10000, Train Loss: 1.1128, Train Accuracy: 0.8013, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6250/10000, Train Loss: 1.1241, Train Accuracy: 0.7902, Val Loss: 1.1976, Val Accuracy: 0.7054
Epoch 6251/10000, Train Loss: 1.1169, Train Accuracy: 0.8025, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6252/10000, Train Loss: 1.1201, Train Accuracy: 0.7958, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6253/10000, Train Loss: 1.1164, Train Accuracy: 0.7902, Val Loss: 1.1973, Val Accuracy: 0.7098
Epoch 6254/10000, Train Loss: 1.1062, Train Accuracy: 0.8092, Val Loss: 1.1973, Val Accuracy: 0.7143
Epoch 6255/10000, Train Loss: 1.1180, Train Accuracy: 0.7958, Val Loss: 1.1974, Val Accuracy: 0.7143
Epoch 6256/10000, Train Loss: 1.1143, Train Accuracy: 0.8036, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6257/10000, Train Loss: 1.1075, Train Accuracy: 0.8080, Val Loss: 1.1979, Val Accuracy: 0.7098
Epoch 6258/10000, Train Loss: 1.1125, Train Accuracy: 0.8013, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6259/10000, Train Loss: 1.1041, Train Accuracy: 0.8170, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6260/10000, Train Loss: 1.1069, Train Accuracy: 0.8114, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6261/10000, Train Loss: 1.1040, Train Accuracy: 0.8125, Val Loss: 1.1976, Val Accuracy: 0.7143
Epoch 6262/10000, Train Loss: 1.1170, Train Accuracy: 0.7946, Val Loss: 1.1978, Val Accuracy: 0.7143
Epoch 6263/10000, Train Loss: 1.1072, Train Accuracy: 0.8047, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6264/10000, Train Loss: 1.1123, Train Accuracy: 0.8013, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6265/10000, Train Loss: 1.1059, Train Accuracy: 0.8047, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6266/10000, Train Loss: 1.1061, Train Accuracy: 0.8069, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6267/10000, Train Loss: 1.1031, Train Accuracy: 0.8058, Val Loss: 1.1977, Val Accuracy: 0.7098
Epoch 6268/10000, Train Loss: 1.1139, Train Accuracy: 0.8002, Val Loss: 1.1977, Val Accuracy: 0.7143
Epoch 6269/10000, Train Loss: 1.1252, Train Accuracy: 0.7935, Val Loss: 1.1976, Val Accuracy: 0.7143
Epoch 6270/10000, Train Loss: 1.1082, Train Accuracy: 0.8103, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6271/10000, Train Loss: 1.1134, Train Accuracy: 0.7980, Val Loss: 1.1972, Val Accuracy: 0.7143
Epoch 6272/10000, Train Loss: 1.0998, Train Accuracy: 0.8181, Val Loss: 1.1972, Val Accuracy: 0.7098
Epoch 6273/10000, Train Loss: 1.1190, Train Accuracy: 0.7958, Val Loss: 1.1974, Val Accuracy: 0.7143
Epoch 6274/10000, Train Loss: 1.0974, Train Accuracy: 0.8203, Val Loss: 1.1972, Val Accuracy: 0.7143
Epoch 6275/10000, Train Loss: 1.1193, Train Accuracy: 0.7879, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6276/10000, Train Loss: 1.1146, Train Accuracy: 0.7958, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6277/10000, Train Loss: 1.1100, Train Accuracy: 0.8080, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6278/10000, Train Loss: 1.1148, Train Accuracy: 0.7958, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6279/10000, Train Loss: 1.1135, Train Accuracy: 0.7935, Val Loss: 1.1974, Val Accuracy: 0.7143
Epoch 6280/10000, Train Loss: 1.1181, Train Accuracy: 0.7980, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6281/10000, Train Loss: 1.1106, Train Accuracy: 0.8025, Val Loss: 1.1972, Val Accuracy: 0.7098
Epoch 6282/10000, Train Loss: 1.1035, Train Accuracy: 0.8080, Val Loss: 1.1972, Val Accuracy: 0.7098
Epoch 6283/10000, Train Loss: 1.1072, Train Accuracy: 0.8069, Val Loss: 1.1974, Val Accuracy: 0.7098
Epoch 6284/10000, Train Loss: 1.1192, Train Accuracy: 0.7958, Val Loss: 1.1975, Val Accuracy: 0.7098
Epoch 6285/10000, Train Loss: 1.1056, Train Accuracy: 0.8147, Val Loss: 1.1975, Val Accuracy: 0.7143
Epoch 6286/10000, Train Loss: 1.1189, Train Accuracy: 0.7891, Val Loss: 1.1976, Val Accuracy: 0.7143
Epoch 6287/10000, Train Loss: 1.1224, Train Accuracy: 0.7913, Val Loss: 1.1976, Val Accuracy: 0.7098
Epoch 6288/10000, Train Loss: 1.1096, Train Accuracy: 0.8058, Val Loss: 1.1974, Val Accuracy: 0.7188
Epoch 6289/10000, Train Loss: 1.1283, Train Accuracy: 0.7824, Val Loss: 1.1973, Val Accuracy: 0.7188
Epoch 6290/10000, Train Loss: 1.1136, Train Accuracy: 0.7980, Val Loss: 1.1972, Val Accuracy: 0.7143
Epoch 6291/10000, Train Loss: 1.1171, Train Accuracy: 0.7969, Val Loss: 1.1968, Val Accuracy: 0.7143
Epoch 6292/10000, Train Loss: 1.1052, Train Accuracy: 0.8069, Val Loss: 1.1965, Val Accuracy: 0.7143
Epoch 6293/10000, Train Loss: 1.1175, Train Accuracy: 0.8002, Val Loss: 1.1966, Val Accuracy: 0.7188
Epoch 6294/10000, Train Loss: 1.1128, Train Accuracy: 0.7980, Val Loss: 1.1964, Val Accuracy: 0.7188
Epoch 6295/10000, Train Loss: 1.1062, Train Accuracy: 0.8103, Val Loss: 1.1960, Val Accuracy: 0.7188
Epoch 6296/10000, Train Loss: 1.1089, Train Accuracy: 0.7980, Val Loss: 1.1959, Val Accuracy: 0.7143
Epoch 6297/10000, Train Loss: 1.1165, Train Accuracy: 0.7991, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6298/10000, Train Loss: 1.1069, Train Accuracy: 0.8114, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6299/10000, Train Loss: 1.0977, Train Accuracy: 0.8181, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6300/10000, Train Loss: 1.1077, Train Accuracy: 0.8047, Val Loss: 1.1957, Val Accuracy: 0.7232
Epoch 6301/10000, Train Loss: 1.1053, Train Accuracy: 0.8058, Val Loss: 1.1955, Val Accuracy: 0.7232
Epoch 6302/10000, Train Loss: 1.1094, Train Accuracy: 0.8013, Val Loss: 1.1952, Val Accuracy: 0.7188
Epoch 6303/10000, Train Loss: 1.1164, Train Accuracy: 0.8002, Val Loss: 1.1952, Val Accuracy: 0.7143
Epoch 6304/10000, Train Loss: 1.1102, Train Accuracy: 0.8069, Val Loss: 1.1949, Val Accuracy: 0.7188
Epoch 6305/10000, Train Loss: 1.1086, Train Accuracy: 0.8092, Val Loss: 1.1950, Val Accuracy: 0.7188
Epoch 6306/10000, Train Loss: 1.1058, Train Accuracy: 0.8147, Val Loss: 1.1947, Val Accuracy: 0.7188
Epoch 6307/10000, Train Loss: 1.1015, Train Accuracy: 0.8136, Val Loss: 1.1947, Val Accuracy: 0.7188
Epoch 6308/10000, Train Loss: 1.1134, Train Accuracy: 0.8002, Val Loss: 1.1947, Val Accuracy: 0.7188
Epoch 6309/10000, Train Loss: 1.1158, Train Accuracy: 0.7991, Val Loss: 1.1948, Val Accuracy: 0.7188
Epoch 6310/10000, Train Loss: 1.1122, Train Accuracy: 0.7946, Val Loss: 1.1950, Val Accuracy: 0.7232
Epoch 6311/10000, Train Loss: 1.1051, Train Accuracy: 0.8136, Val Loss: 1.1950, Val Accuracy: 0.7232
Epoch 6312/10000, Train Loss: 1.1077, Train Accuracy: 0.8069, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6313/10000, Train Loss: 1.1127, Train Accuracy: 0.8036, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6314/10000, Train Loss: 1.1160, Train Accuracy: 0.7991, Val Loss: 1.1958, Val Accuracy: 0.7232
Epoch 6315/10000, Train Loss: 1.1064, Train Accuracy: 0.8047, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6316/10000, Train Loss: 1.1075, Train Accuracy: 0.8125, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6317/10000, Train Loss: 1.1144, Train Accuracy: 0.8080, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6318/10000, Train Loss: 1.1130, Train Accuracy: 0.8058, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6319/10000, Train Loss: 1.1118, Train Accuracy: 0.8025, Val Loss: 1.1955, Val Accuracy: 0.7143
Epoch 6320/10000, Train Loss: 1.1127, Train Accuracy: 0.7924, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6321/10000, Train Loss: 1.1193, Train Accuracy: 0.7991, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6322/10000, Train Loss: 1.1116, Train Accuracy: 0.8002, Val Loss: 1.1951, Val Accuracy: 0.7232
Epoch 6323/10000, Train Loss: 1.1006, Train Accuracy: 0.8203, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6324/10000, Train Loss: 1.1149, Train Accuracy: 0.8002, Val Loss: 1.1952, Val Accuracy: 0.7232
Epoch 6325/10000, Train Loss: 1.1107, Train Accuracy: 0.8080, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6326/10000, Train Loss: 1.1172, Train Accuracy: 0.8036, Val Loss: 1.1952, Val Accuracy: 0.7188
Epoch 6327/10000, Train Loss: 1.1059, Train Accuracy: 0.8092, Val Loss: 1.1954, Val Accuracy: 0.7232
Epoch 6328/10000, Train Loss: 1.1221, Train Accuracy: 0.7857, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6329/10000, Train Loss: 1.1162, Train Accuracy: 0.7946, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6330/10000, Train Loss: 1.1123, Train Accuracy: 0.8147, Val Loss: 1.1953, Val Accuracy: 0.7188
Epoch 6331/10000, Train Loss: 1.0992, Train Accuracy: 0.8248, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6332/10000, Train Loss: 1.1024, Train Accuracy: 0.8147, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6333/10000, Train Loss: 1.1081, Train Accuracy: 0.8025, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6334/10000, Train Loss: 1.0941, Train Accuracy: 0.8147, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6335/10000, Train Loss: 1.1051, Train Accuracy: 0.8080, Val Loss: 1.1954, Val Accuracy: 0.7232
Epoch 6336/10000, Train Loss: 1.1167, Train Accuracy: 0.7868, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6337/10000, Train Loss: 1.1065, Train Accuracy: 0.8114, Val Loss: 1.1952, Val Accuracy: 0.7188
Epoch 6338/10000, Train Loss: 1.1144, Train Accuracy: 0.7980, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6339/10000, Train Loss: 1.1090, Train Accuracy: 0.8036, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6340/10000, Train Loss: 1.1078, Train Accuracy: 0.8047, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6341/10000, Train Loss: 1.1133, Train Accuracy: 0.8058, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6342/10000, Train Loss: 1.1058, Train Accuracy: 0.8047, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6343/10000, Train Loss: 1.1005, Train Accuracy: 0.8181, Val Loss: 1.1956, Val Accuracy: 0.7143
Epoch 6344/10000, Train Loss: 1.1119, Train Accuracy: 0.8103, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6345/10000, Train Loss: 1.1061, Train Accuracy: 0.8103, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6346/10000, Train Loss: 1.1134, Train Accuracy: 0.7946, Val Loss: 1.1959, Val Accuracy: 0.7188
Epoch 6347/10000, Train Loss: 1.1041, Train Accuracy: 0.8080, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6348/10000, Train Loss: 1.0967, Train Accuracy: 0.8214, Val Loss: 1.1956, Val Accuracy: 0.7143
Epoch 6349/10000, Train Loss: 1.1089, Train Accuracy: 0.8080, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6350/10000, Train Loss: 1.1053, Train Accuracy: 0.8125, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6351/10000, Train Loss: 1.1008, Train Accuracy: 0.8147, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6352/10000, Train Loss: 1.1160, Train Accuracy: 0.7958, Val Loss: 1.1954, Val Accuracy: 0.7143
Epoch 6353/10000, Train Loss: 1.1154, Train Accuracy: 0.7946, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6354/10000, Train Loss: 1.0999, Train Accuracy: 0.8158, Val Loss: 1.1960, Val Accuracy: 0.7143
Epoch 6355/10000, Train Loss: 1.1121, Train Accuracy: 0.8025, Val Loss: 1.1959, Val Accuracy: 0.7188
Epoch 6356/10000, Train Loss: 1.1005, Train Accuracy: 0.8158, Val Loss: 1.1959, Val Accuracy: 0.7143
Epoch 6357/10000, Train Loss: 1.0948, Train Accuracy: 0.8181, Val Loss: 1.1959, Val Accuracy: 0.7143
Epoch 6358/10000, Train Loss: 1.1238, Train Accuracy: 0.7868, Val Loss: 1.1959, Val Accuracy: 0.7143
Epoch 6359/10000, Train Loss: 1.1113, Train Accuracy: 0.8080, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6360/10000, Train Loss: 1.1036, Train Accuracy: 0.8058, Val Loss: 1.1956, Val Accuracy: 0.7143
Epoch 6361/10000, Train Loss: 1.1013, Train Accuracy: 0.8147, Val Loss: 1.1955, Val Accuracy: 0.7143
Epoch 6362/10000, Train Loss: 1.1150, Train Accuracy: 0.7991, Val Loss: 1.1954, Val Accuracy: 0.7143
Epoch 6363/10000, Train Loss: 1.1065, Train Accuracy: 0.8103, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6364/10000, Train Loss: 1.1081, Train Accuracy: 0.8103, Val Loss: 1.1953, Val Accuracy: 0.7188
Epoch 6365/10000, Train Loss: 1.1203, Train Accuracy: 0.7902, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6366/10000, Train Loss: 1.1064, Train Accuracy: 0.8069, Val Loss: 1.1954, Val Accuracy: 0.7143
Epoch 6367/10000, Train Loss: 1.1001, Train Accuracy: 0.8147, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6368/10000, Train Loss: 1.1108, Train Accuracy: 0.8002, Val Loss: 1.1955, Val Accuracy: 0.7143
Epoch 6369/10000, Train Loss: 1.0957, Train Accuracy: 0.8270, Val Loss: 1.1955, Val Accuracy: 0.7143
Epoch 6370/10000, Train Loss: 1.1100, Train Accuracy: 0.8025, Val Loss: 1.1952, Val Accuracy: 0.7098
Epoch 6371/10000, Train Loss: 1.1068, Train Accuracy: 0.8025, Val Loss: 1.1952, Val Accuracy: 0.7143
Epoch 6372/10000, Train Loss: 1.1103, Train Accuracy: 0.7924, Val Loss: 1.1956, Val Accuracy: 0.7098
Epoch 6373/10000, Train Loss: 1.1081, Train Accuracy: 0.8069, Val Loss: 1.1959, Val Accuracy: 0.7143
Epoch 6374/10000, Train Loss: 1.1035, Train Accuracy: 0.8080, Val Loss: 1.1957, Val Accuracy: 0.7143
Epoch 6375/10000, Train Loss: 1.1093, Train Accuracy: 0.8025, Val Loss: 1.1960, Val Accuracy: 0.7143
Epoch 6376/10000, Train Loss: 1.1099, Train Accuracy: 0.8058, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6377/10000, Train Loss: 1.1004, Train Accuracy: 0.8170, Val Loss: 1.1960, Val Accuracy: 0.7143
Epoch 6378/10000, Train Loss: 1.1116, Train Accuracy: 0.7946, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6379/10000, Train Loss: 1.1014, Train Accuracy: 0.8136, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6380/10000, Train Loss: 1.1083, Train Accuracy: 0.8080, Val Loss: 1.1958, Val Accuracy: 0.7232
Epoch 6381/10000, Train Loss: 1.1125, Train Accuracy: 0.8025, Val Loss: 1.1955, Val Accuracy: 0.7232
Epoch 6382/10000, Train Loss: 1.1145, Train Accuracy: 0.8025, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6383/10000, Train Loss: 1.1093, Train Accuracy: 0.7980, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6384/10000, Train Loss: 1.1002, Train Accuracy: 0.8125, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6385/10000, Train Loss: 1.1132, Train Accuracy: 0.8047, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6386/10000, Train Loss: 1.1045, Train Accuracy: 0.8158, Val Loss: 1.1955, Val Accuracy: 0.7143
Epoch 6387/10000, Train Loss: 1.0877, Train Accuracy: 0.8326, Val Loss: 1.1955, Val Accuracy: 0.7232
Epoch 6388/10000, Train Loss: 1.1177, Train Accuracy: 0.7980, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6389/10000, Train Loss: 1.1047, Train Accuracy: 0.8103, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6390/10000, Train Loss: 1.1061, Train Accuracy: 0.8013, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6391/10000, Train Loss: 1.0969, Train Accuracy: 0.8158, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6392/10000, Train Loss: 1.0959, Train Accuracy: 0.8136, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6393/10000, Train Loss: 1.1036, Train Accuracy: 0.8125, Val Loss: 1.1955, Val Accuracy: 0.7188
Epoch 6394/10000, Train Loss: 1.1065, Train Accuracy: 0.8025, Val Loss: 1.1958, Val Accuracy: 0.7188
Epoch 6395/10000, Train Loss: 1.0924, Train Accuracy: 0.8270, Val Loss: 1.1959, Val Accuracy: 0.7188
Epoch 6396/10000, Train Loss: 1.1056, Train Accuracy: 0.8203, Val Loss: 1.1960, Val Accuracy: 0.7232
Epoch 6397/10000, Train Loss: 1.1052, Train Accuracy: 0.8058, Val Loss: 1.1959, Val Accuracy: 0.7232
Epoch 6398/10000, Train Loss: 1.0989, Train Accuracy: 0.8136, Val Loss: 1.1958, Val Accuracy: 0.7277
Epoch 6399/10000, Train Loss: 1.1012, Train Accuracy: 0.8092, Val Loss: 1.1954, Val Accuracy: 0.7277
Epoch 6400/10000, Train Loss: 1.0886, Train Accuracy: 0.8326, Val Loss: 1.1957, Val Accuracy: 0.7232
Epoch 6401/10000, Train Loss: 1.1094, Train Accuracy: 0.8080, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6402/10000, Train Loss: 1.1093, Train Accuracy: 0.8025, Val Loss: 1.1957, Val Accuracy: 0.7188
Epoch 6403/10000, Train Loss: 1.0947, Train Accuracy: 0.8237, Val Loss: 1.1958, Val Accuracy: 0.7232
Epoch 6404/10000, Train Loss: 1.1113, Train Accuracy: 0.8114, Val Loss: 1.1953, Val Accuracy: 0.7232
Epoch 6405/10000, Train Loss: 1.0933, Train Accuracy: 0.8225, Val Loss: 1.1954, Val Accuracy: 0.7232
Epoch 6406/10000, Train Loss: 1.1064, Train Accuracy: 0.8080, Val Loss: 1.1952, Val Accuracy: 0.7232
Epoch 6407/10000, Train Loss: 1.1007, Train Accuracy: 0.8203, Val Loss: 1.1952, Val Accuracy: 0.7232
Epoch 6408/10000, Train Loss: 1.1036, Train Accuracy: 0.8058, Val Loss: 1.1951, Val Accuracy: 0.7232
Epoch 6409/10000, Train Loss: 1.1050, Train Accuracy: 0.8092, Val Loss: 1.1949, Val Accuracy: 0.7232
Epoch 6410/10000, Train Loss: 1.1087, Train Accuracy: 0.8058, Val Loss: 1.1950, Val Accuracy: 0.7232
Epoch 6411/10000, Train Loss: 1.0949, Train Accuracy: 0.8192, Val Loss: 1.1951, Val Accuracy: 0.7232
Epoch 6412/10000, Train Loss: 1.1131, Train Accuracy: 0.8002, Val Loss: 1.1950, Val Accuracy: 0.7232
Epoch 6413/10000, Train Loss: 1.1034, Train Accuracy: 0.8114, Val Loss: 1.1948, Val Accuracy: 0.7277
Epoch 6414/10000, Train Loss: 1.1097, Train Accuracy: 0.8025, Val Loss: 1.1951, Val Accuracy: 0.7277
Epoch 6415/10000, Train Loss: 1.1117, Train Accuracy: 0.8025, Val Loss: 1.1950, Val Accuracy: 0.7232
Epoch 6416/10000, Train Loss: 1.1031, Train Accuracy: 0.8092, Val Loss: 1.1952, Val Accuracy: 0.7232
Epoch 6417/10000, Train Loss: 1.0977, Train Accuracy: 0.8170, Val Loss: 1.1954, Val Accuracy: 0.7232
Epoch 6418/10000, Train Loss: 1.1156, Train Accuracy: 0.7902, Val Loss: 1.1955, Val Accuracy: 0.7277
Epoch 6419/10000, Train Loss: 1.1093, Train Accuracy: 0.8013, Val Loss: 1.1957, Val Accuracy: 0.7277
Epoch 6420/10000, Train Loss: 1.1010, Train Accuracy: 0.8125, Val Loss: 1.1957, Val Accuracy: 0.7277
Epoch 6421/10000, Train Loss: 1.1118, Train Accuracy: 0.7958, Val Loss: 1.1957, Val Accuracy: 0.7277
Epoch 6422/10000, Train Loss: 1.1115, Train Accuracy: 0.7935, Val Loss: 1.1958, Val Accuracy: 0.7143
Epoch 6423/10000, Train Loss: 1.1065, Train Accuracy: 0.7980, Val Loss: 1.1956, Val Accuracy: 0.7232
Epoch 6424/10000, Train Loss: 1.1088, Train Accuracy: 0.7980, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6425/10000, Train Loss: 1.0900, Train Accuracy: 0.8304, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6426/10000, Train Loss: 1.0977, Train Accuracy: 0.8181, Val Loss: 1.1956, Val Accuracy: 0.7188
Epoch 6427/10000, Train Loss: 1.1080, Train Accuracy: 0.8047, Val Loss: 1.1954, Val Accuracy: 0.7188
Epoch 6428/10000, Train Loss: 1.1136, Train Accuracy: 0.7991, Val Loss: 1.1949, Val Accuracy: 0.7098
Epoch 6429/10000, Train Loss: 1.1027, Train Accuracy: 0.8181, Val Loss: 1.1946, Val Accuracy: 0.7188
Epoch 6430/10000, Train Loss: 1.1018, Train Accuracy: 0.8147, Val Loss: 1.1946, Val Accuracy: 0.7143
Epoch 6431/10000, Train Loss: 1.0995, Train Accuracy: 0.8147, Val Loss: 1.1947, Val Accuracy: 0.7143
Epoch 6432/10000, Train Loss: 1.1088, Train Accuracy: 0.8069, Val Loss: 1.1945, Val Accuracy: 0.7188
Epoch 6433/10000, Train Loss: 1.0945, Train Accuracy: 0.8237, Val Loss: 1.1945, Val Accuracy: 0.7277
Epoch 6434/10000, Train Loss: 1.1027, Train Accuracy: 0.8136, Val Loss: 1.1946, Val Accuracy: 0.7232
Epoch 6435/10000, Train Loss: 1.0888, Train Accuracy: 0.8337, Val Loss: 1.1944, Val Accuracy: 0.7277
Epoch 6436/10000, Train Loss: 1.0995, Train Accuracy: 0.8147, Val Loss: 1.1943, Val Accuracy: 0.7232
Epoch 6437/10000, Train Loss: 1.1058, Train Accuracy: 0.8036, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6438/10000, Train Loss: 1.1166, Train Accuracy: 0.7969, Val Loss: 1.1940, Val Accuracy: 0.7277
Epoch 6439/10000, Train Loss: 1.1044, Train Accuracy: 0.8125, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6440/10000, Train Loss: 1.1127, Train Accuracy: 0.7991, Val Loss: 1.1942, Val Accuracy: 0.7277
Epoch 6441/10000, Train Loss: 1.0974, Train Accuracy: 0.8170, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6442/10000, Train Loss: 1.1153, Train Accuracy: 0.7991, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6443/10000, Train Loss: 1.1019, Train Accuracy: 0.8114, Val Loss: 1.1944, Val Accuracy: 0.7232
Epoch 6444/10000, Train Loss: 1.1105, Train Accuracy: 0.8103, Val Loss: 1.1946, Val Accuracy: 0.7232
Epoch 6445/10000, Train Loss: 1.0960, Train Accuracy: 0.8147, Val Loss: 1.1949, Val Accuracy: 0.7232
Epoch 6446/10000, Train Loss: 1.1026, Train Accuracy: 0.8103, Val Loss: 1.1948, Val Accuracy: 0.7232
Epoch 6447/10000, Train Loss: 1.1074, Train Accuracy: 0.8047, Val Loss: 1.1944, Val Accuracy: 0.7232
Epoch 6448/10000, Train Loss: 1.1146, Train Accuracy: 0.7991, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6449/10000, Train Loss: 1.1061, Train Accuracy: 0.8114, Val Loss: 1.1942, Val Accuracy: 0.7188
Epoch 6450/10000, Train Loss: 1.1117, Train Accuracy: 0.8036, Val Loss: 1.1939, Val Accuracy: 0.7232
Epoch 6451/10000, Train Loss: 1.1089, Train Accuracy: 0.7980, Val Loss: 1.1940, Val Accuracy: 0.7277
Epoch 6452/10000, Train Loss: 1.0965, Train Accuracy: 0.8214, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6453/10000, Train Loss: 1.1144, Train Accuracy: 0.7868, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6454/10000, Train Loss: 1.0932, Train Accuracy: 0.8170, Val Loss: 1.1937, Val Accuracy: 0.7232
Epoch 6455/10000, Train Loss: 1.1067, Train Accuracy: 0.8103, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6456/10000, Train Loss: 1.1066, Train Accuracy: 0.8047, Val Loss: 1.1940, Val Accuracy: 0.7232
Epoch 6457/10000, Train Loss: 1.0962, Train Accuracy: 0.8147, Val Loss: 1.1938, Val Accuracy: 0.7321
Epoch 6458/10000, Train Loss: 1.1083, Train Accuracy: 0.8092, Val Loss: 1.1938, Val Accuracy: 0.7321
Epoch 6459/10000, Train Loss: 1.1183, Train Accuracy: 0.7958, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6460/10000, Train Loss: 1.1071, Train Accuracy: 0.8125, Val Loss: 1.1939, Val Accuracy: 0.7277
Epoch 6461/10000, Train Loss: 1.1007, Train Accuracy: 0.8225, Val Loss: 1.1940, Val Accuracy: 0.7277
Epoch 6462/10000, Train Loss: 1.1000, Train Accuracy: 0.8170, Val Loss: 1.1943, Val Accuracy: 0.7277
Epoch 6463/10000, Train Loss: 1.0940, Train Accuracy: 0.8147, Val Loss: 1.1941, Val Accuracy: 0.7232
Epoch 6464/10000, Train Loss: 1.0981, Train Accuracy: 0.8136, Val Loss: 1.1939, Val Accuracy: 0.7277
Epoch 6465/10000, Train Loss: 1.1009, Train Accuracy: 0.8147, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6466/10000, Train Loss: 1.0970, Train Accuracy: 0.8237, Val Loss: 1.1941, Val Accuracy: 0.7232
Epoch 6467/10000, Train Loss: 1.1121, Train Accuracy: 0.7991, Val Loss: 1.1943, Val Accuracy: 0.7277
Epoch 6468/10000, Train Loss: 1.1007, Train Accuracy: 0.8158, Val Loss: 1.1940, Val Accuracy: 0.7321
Epoch 6469/10000, Train Loss: 1.1034, Train Accuracy: 0.8058, Val Loss: 1.1942, Val Accuracy: 0.7277
Epoch 6470/10000, Train Loss: 1.0915, Train Accuracy: 0.8192, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6471/10000, Train Loss: 1.0946, Train Accuracy: 0.8158, Val Loss: 1.1942, Val Accuracy: 0.7277
Epoch 6472/10000, Train Loss: 1.1093, Train Accuracy: 0.8080, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6473/10000, Train Loss: 1.0828, Train Accuracy: 0.8337, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6474/10000, Train Loss: 1.1150, Train Accuracy: 0.8013, Val Loss: 1.1941, Val Accuracy: 0.7321
Epoch 6475/10000, Train Loss: 1.0982, Train Accuracy: 0.8136, Val Loss: 1.1938, Val Accuracy: 0.7277
Epoch 6476/10000, Train Loss: 1.1050, Train Accuracy: 0.8170, Val Loss: 1.1940, Val Accuracy: 0.7277
Epoch 6477/10000, Train Loss: 1.1019, Train Accuracy: 0.8103, Val Loss: 1.1933, Val Accuracy: 0.7277
Epoch 6478/10000, Train Loss: 1.1069, Train Accuracy: 0.8069, Val Loss: 1.1934, Val Accuracy: 0.7321
Epoch 6479/10000, Train Loss: 1.0999, Train Accuracy: 0.8203, Val Loss: 1.1936, Val Accuracy: 0.7232
Epoch 6480/10000, Train Loss: 1.1080, Train Accuracy: 0.7958, Val Loss: 1.1937, Val Accuracy: 0.7232
Epoch 6481/10000, Train Loss: 1.1165, Train Accuracy: 0.7958, Val Loss: 1.1934, Val Accuracy: 0.7188
Epoch 6482/10000, Train Loss: 1.1039, Train Accuracy: 0.8114, Val Loss: 1.1936, Val Accuracy: 0.7232
Epoch 6483/10000, Train Loss: 1.1118, Train Accuracy: 0.7991, Val Loss: 1.1934, Val Accuracy: 0.7232
Epoch 6484/10000, Train Loss: 1.0852, Train Accuracy: 0.8393, Val Loss: 1.1932, Val Accuracy: 0.7232
Epoch 6485/10000, Train Loss: 1.1053, Train Accuracy: 0.8058, Val Loss: 1.1936, Val Accuracy: 0.7232
Epoch 6486/10000, Train Loss: 1.1012, Train Accuracy: 0.8147, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6487/10000, Train Loss: 1.1078, Train Accuracy: 0.8080, Val Loss: 1.1938, Val Accuracy: 0.7232
Epoch 6488/10000, Train Loss: 1.0961, Train Accuracy: 0.8203, Val Loss: 1.1939, Val Accuracy: 0.7232
Epoch 6489/10000, Train Loss: 1.1019, Train Accuracy: 0.8125, Val Loss: 1.1937, Val Accuracy: 0.7232
Epoch 6490/10000, Train Loss: 1.1085, Train Accuracy: 0.8158, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6491/10000, Train Loss: 1.1070, Train Accuracy: 0.8069, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6492/10000, Train Loss: 1.0984, Train Accuracy: 0.8192, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6493/10000, Train Loss: 1.1000, Train Accuracy: 0.8170, Val Loss: 1.1938, Val Accuracy: 0.7232
Epoch 6494/10000, Train Loss: 1.1187, Train Accuracy: 0.7902, Val Loss: 1.1940, Val Accuracy: 0.7188
Epoch 6495/10000, Train Loss: 1.0961, Train Accuracy: 0.8170, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6496/10000, Train Loss: 1.0994, Train Accuracy: 0.8125, Val Loss: 1.1942, Val Accuracy: 0.7232
Epoch 6497/10000, Train Loss: 1.1019, Train Accuracy: 0.8136, Val Loss: 1.1943, Val Accuracy: 0.7232
Epoch 6498/10000, Train Loss: 1.1062, Train Accuracy: 0.8103, Val Loss: 1.1943, Val Accuracy: 0.7188
Epoch 6499/10000, Train Loss: 1.0991, Train Accuracy: 0.8047, Val Loss: 1.1941, Val Accuracy: 0.7188
Epoch 6500/10000, Train Loss: 1.1008, Train Accuracy: 0.8136, Val Loss: 1.1940, Val Accuracy: 0.7232
Epoch 6501/10000, Train Loss: 1.1154, Train Accuracy: 0.7991, Val Loss: 1.1940, Val Accuracy: 0.7232
Epoch 6502/10000, Train Loss: 1.1020, Train Accuracy: 0.8147, Val Loss: 1.1940, Val Accuracy: 0.7277
Epoch 6503/10000, Train Loss: 1.0848, Train Accuracy: 0.8348, Val Loss: 1.1938, Val Accuracy: 0.7277
Epoch 6504/10000, Train Loss: 1.1078, Train Accuracy: 0.8069, Val Loss: 1.1938, Val Accuracy: 0.7277
Epoch 6505/10000, Train Loss: 1.1115, Train Accuracy: 0.8058, Val Loss: 1.1939, Val Accuracy: 0.7232
Epoch 6506/10000, Train Loss: 1.1025, Train Accuracy: 0.8147, Val Loss: 1.1941, Val Accuracy: 0.7277
Epoch 6507/10000, Train Loss: 1.1114, Train Accuracy: 0.8002, Val Loss: 1.1942, Val Accuracy: 0.7188
Epoch 6508/10000, Train Loss: 1.1008, Train Accuracy: 0.8192, Val Loss: 1.1945, Val Accuracy: 0.7232
Epoch 6509/10000, Train Loss: 1.1184, Train Accuracy: 0.7958, Val Loss: 1.1942, Val Accuracy: 0.7277
Epoch 6510/10000, Train Loss: 1.1078, Train Accuracy: 0.8069, Val Loss: 1.1939, Val Accuracy: 0.7277
Epoch 6511/10000, Train Loss: 1.0978, Train Accuracy: 0.8136, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6512/10000, Train Loss: 1.1080, Train Accuracy: 0.8080, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6513/10000, Train Loss: 1.1095, Train Accuracy: 0.8069, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6514/10000, Train Loss: 1.0996, Train Accuracy: 0.8214, Val Loss: 1.1934, Val Accuracy: 0.7277
Epoch 6515/10000, Train Loss: 1.1059, Train Accuracy: 0.8114, Val Loss: 1.1938, Val Accuracy: 0.7277
Epoch 6516/10000, Train Loss: 1.0964, Train Accuracy: 0.8203, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6517/10000, Train Loss: 1.0969, Train Accuracy: 0.8281, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6518/10000, Train Loss: 1.0946, Train Accuracy: 0.8170, Val Loss: 1.1937, Val Accuracy: 0.7277
Epoch 6519/10000, Train Loss: 1.1041, Train Accuracy: 0.8047, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6520/10000, Train Loss: 1.1087, Train Accuracy: 0.8036, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6521/10000, Train Loss: 1.0983, Train Accuracy: 0.8136, Val Loss: 1.1934, Val Accuracy: 0.7277
Epoch 6522/10000, Train Loss: 1.0890, Train Accuracy: 0.8281, Val Loss: 1.1932, Val Accuracy: 0.7277
Epoch 6523/10000, Train Loss: 1.1004, Train Accuracy: 0.8147, Val Loss: 1.1934, Val Accuracy: 0.7277
Epoch 6524/10000, Train Loss: 1.1115, Train Accuracy: 0.7969, Val Loss: 1.1934, Val Accuracy: 0.7277
Epoch 6525/10000, Train Loss: 1.1016, Train Accuracy: 0.8080, Val Loss: 1.1932, Val Accuracy: 0.7277
Epoch 6526/10000, Train Loss: 1.0928, Train Accuracy: 0.8203, Val Loss: 1.1930, Val Accuracy: 0.7277
Epoch 6527/10000, Train Loss: 1.1097, Train Accuracy: 0.7913, Val Loss: 1.1930, Val Accuracy: 0.7277
Epoch 6528/10000, Train Loss: 1.1190, Train Accuracy: 0.7969, Val Loss: 1.1932, Val Accuracy: 0.7277
Epoch 6529/10000, Train Loss: 1.1009, Train Accuracy: 0.8103, Val Loss: 1.1934, Val Accuracy: 0.7277
Epoch 6530/10000, Train Loss: 1.0920, Train Accuracy: 0.8259, Val Loss: 1.1932, Val Accuracy: 0.7277
Epoch 6531/10000, Train Loss: 1.1052, Train Accuracy: 0.8013, Val Loss: 1.1936, Val Accuracy: 0.7277
Epoch 6532/10000, Train Loss: 1.0986, Train Accuracy: 0.8147, Val Loss: 1.1936, Val Accuracy: 0.7232
Epoch 6533/10000, Train Loss: 1.1128, Train Accuracy: 0.7935, Val Loss: 1.1935, Val Accuracy: 0.7188
Epoch 6534/10000, Train Loss: 1.1018, Train Accuracy: 0.8225, Val Loss: 1.1935, Val Accuracy: 0.7188
Epoch 6535/10000, Train Loss: 1.1052, Train Accuracy: 0.8125, Val Loss: 1.1930, Val Accuracy: 0.7188
Epoch 6536/10000, Train Loss: 1.1076, Train Accuracy: 0.8092, Val Loss: 1.1929, Val Accuracy: 0.7232
Epoch 6537/10000, Train Loss: 1.1001, Train Accuracy: 0.8158, Val Loss: 1.1933, Val Accuracy: 0.7232
Epoch 6538/10000, Train Loss: 1.1098, Train Accuracy: 0.8036, Val Loss: 1.1930, Val Accuracy: 0.7188
Epoch 6539/10000, Train Loss: 1.1055, Train Accuracy: 0.8092, Val Loss: 1.1928, Val Accuracy: 0.7188
Epoch 6540/10000, Train Loss: 1.1078, Train Accuracy: 0.8002, Val Loss: 1.1927, Val Accuracy: 0.7188
Epoch 6541/10000, Train Loss: 1.0987, Train Accuracy: 0.8103, Val Loss: 1.1929, Val Accuracy: 0.7188
Epoch 6542/10000, Train Loss: 1.1052, Train Accuracy: 0.8114, Val Loss: 1.1927, Val Accuracy: 0.7143
Epoch 6543/10000, Train Loss: 1.1090, Train Accuracy: 0.8036, Val Loss: 1.1928, Val Accuracy: 0.7188
Epoch 6544/10000, Train Loss: 1.1088, Train Accuracy: 0.8025, Val Loss: 1.1931, Val Accuracy: 0.7188
Epoch 6545/10000, Train Loss: 1.1023, Train Accuracy: 0.8170, Val Loss: 1.1930, Val Accuracy: 0.7188
Epoch 6546/10000, Train Loss: 1.1013, Train Accuracy: 0.8181, Val Loss: 1.1931, Val Accuracy: 0.7188
Epoch 6547/10000, Train Loss: 1.1087, Train Accuracy: 0.8047, Val Loss: 1.1930, Val Accuracy: 0.7232
Epoch 6548/10000, Train Loss: 1.1064, Train Accuracy: 0.8080, Val Loss: 1.1929, Val Accuracy: 0.7232
Epoch 6549/10000, Train Loss: 1.1075, Train Accuracy: 0.8047, Val Loss: 1.1928, Val Accuracy: 0.7232
Epoch 6550/10000, Train Loss: 1.0870, Train Accuracy: 0.8292, Val Loss: 1.1926, Val Accuracy: 0.7232
Epoch 6551/10000, Train Loss: 1.1039, Train Accuracy: 0.8125, Val Loss: 1.1925, Val Accuracy: 0.7232
Epoch 6552/10000, Train Loss: 1.1050, Train Accuracy: 0.8103, Val Loss: 1.1924, Val Accuracy: 0.7232
Epoch 6553/10000, Train Loss: 1.1023, Train Accuracy: 0.8080, Val Loss: 1.1923, Val Accuracy: 0.7232
Epoch 6554/10000, Train Loss: 1.1076, Train Accuracy: 0.8025, Val Loss: 1.1922, Val Accuracy: 0.7188
Epoch 6555/10000, Train Loss: 1.1013, Train Accuracy: 0.8114, Val Loss: 1.1924, Val Accuracy: 0.7188
Epoch 6556/10000, Train Loss: 1.0991, Train Accuracy: 0.8136, Val Loss: 1.1924, Val Accuracy: 0.7188
Epoch 6557/10000, Train Loss: 1.1058, Train Accuracy: 0.8147, Val Loss: 1.1924, Val Accuracy: 0.7188
Epoch 6558/10000, Train Loss: 1.1033, Train Accuracy: 0.8036, Val Loss: 1.1923, Val Accuracy: 0.7188
Epoch 6559/10000, Train Loss: 1.1126, Train Accuracy: 0.7991, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6560/10000, Train Loss: 1.0995, Train Accuracy: 0.8214, Val Loss: 1.1920, Val Accuracy: 0.7143
Epoch 6561/10000, Train Loss: 1.0957, Train Accuracy: 0.8181, Val Loss: 1.1921, Val Accuracy: 0.7143
Epoch 6562/10000, Train Loss: 1.0972, Train Accuracy: 0.8147, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6563/10000, Train Loss: 1.1036, Train Accuracy: 0.8069, Val Loss: 1.1921, Val Accuracy: 0.7143
Epoch 6564/10000, Train Loss: 1.1069, Train Accuracy: 0.8069, Val Loss: 1.1923, Val Accuracy: 0.7188
Epoch 6565/10000, Train Loss: 1.0965, Train Accuracy: 0.8192, Val Loss: 1.1924, Val Accuracy: 0.7143
Epoch 6566/10000, Train Loss: 1.1030, Train Accuracy: 0.8092, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6567/10000, Train Loss: 1.0986, Train Accuracy: 0.8214, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6568/10000, Train Loss: 1.1050, Train Accuracy: 0.8069, Val Loss: 1.1929, Val Accuracy: 0.7143
Epoch 6569/10000, Train Loss: 1.1034, Train Accuracy: 0.8114, Val Loss: 1.1928, Val Accuracy: 0.7188
Epoch 6570/10000, Train Loss: 1.1066, Train Accuracy: 0.8114, Val Loss: 1.1927, Val Accuracy: 0.7143
Epoch 6571/10000, Train Loss: 1.0984, Train Accuracy: 0.8158, Val Loss: 1.1927, Val Accuracy: 0.7143
Epoch 6572/10000, Train Loss: 1.0919, Train Accuracy: 0.8237, Val Loss: 1.1926, Val Accuracy: 0.7188
Epoch 6573/10000, Train Loss: 1.0933, Train Accuracy: 0.8225, Val Loss: 1.1926, Val Accuracy: 0.7232
Epoch 6574/10000, Train Loss: 1.1076, Train Accuracy: 0.8092, Val Loss: 1.1927, Val Accuracy: 0.7188
Epoch 6575/10000, Train Loss: 1.1049, Train Accuracy: 0.8080, Val Loss: 1.1926, Val Accuracy: 0.7188
Epoch 6576/10000, Train Loss: 1.1045, Train Accuracy: 0.8147, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6577/10000, Train Loss: 1.1066, Train Accuracy: 0.8025, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6578/10000, Train Loss: 1.0942, Train Accuracy: 0.8214, Val Loss: 1.1924, Val Accuracy: 0.7143
Epoch 6579/10000, Train Loss: 1.1048, Train Accuracy: 0.8080, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6580/10000, Train Loss: 1.0987, Train Accuracy: 0.8259, Val Loss: 1.1928, Val Accuracy: 0.7143
Epoch 6581/10000, Train Loss: 1.1017, Train Accuracy: 0.8103, Val Loss: 1.1930, Val Accuracy: 0.7143
Epoch 6582/10000, Train Loss: 1.0960, Train Accuracy: 0.8203, Val Loss: 1.1929, Val Accuracy: 0.7143
Epoch 6583/10000, Train Loss: 1.0987, Train Accuracy: 0.8069, Val Loss: 1.1928, Val Accuracy: 0.7143
Epoch 6584/10000, Train Loss: 1.0911, Train Accuracy: 0.8237, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6585/10000, Train Loss: 1.1107, Train Accuracy: 0.8058, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6586/10000, Train Loss: 1.0995, Train Accuracy: 0.8080, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6587/10000, Train Loss: 1.1115, Train Accuracy: 0.7969, Val Loss: 1.1927, Val Accuracy: 0.7143
Epoch 6588/10000, Train Loss: 1.1043, Train Accuracy: 0.8092, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6589/10000, Train Loss: 1.0998, Train Accuracy: 0.8136, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6590/10000, Train Loss: 1.1082, Train Accuracy: 0.8025, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6591/10000, Train Loss: 1.0947, Train Accuracy: 0.8259, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6592/10000, Train Loss: 1.0948, Train Accuracy: 0.8214, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6593/10000, Train Loss: 1.1121, Train Accuracy: 0.8069, Val Loss: 1.1924, Val Accuracy: 0.7143
Epoch 6594/10000, Train Loss: 1.0997, Train Accuracy: 0.8170, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6595/10000, Train Loss: 1.0997, Train Accuracy: 0.8136, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6596/10000, Train Loss: 1.0991, Train Accuracy: 0.8092, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6597/10000, Train Loss: 1.0977, Train Accuracy: 0.8237, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6598/10000, Train Loss: 1.0980, Train Accuracy: 0.8136, Val Loss: 1.1926, Val Accuracy: 0.7143
Epoch 6599/10000, Train Loss: 1.1048, Train Accuracy: 0.8092, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6600/10000, Train Loss: 1.1011, Train Accuracy: 0.8080, Val Loss: 1.1924, Val Accuracy: 0.7143
Epoch 6601/10000, Train Loss: 1.1046, Train Accuracy: 0.8058, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6602/10000, Train Loss: 1.0939, Train Accuracy: 0.8170, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6603/10000, Train Loss: 1.1045, Train Accuracy: 0.7991, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6604/10000, Train Loss: 1.1007, Train Accuracy: 0.8136, Val Loss: 1.1920, Val Accuracy: 0.7143
Epoch 6605/10000, Train Loss: 1.0982, Train Accuracy: 0.8214, Val Loss: 1.1920, Val Accuracy: 0.7143
Epoch 6606/10000, Train Loss: 1.1038, Train Accuracy: 0.8103, Val Loss: 1.1923, Val Accuracy: 0.7143
Epoch 6607/10000, Train Loss: 1.0923, Train Accuracy: 0.8237, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6608/10000, Train Loss: 1.1068, Train Accuracy: 0.8025, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6609/10000, Train Loss: 1.0997, Train Accuracy: 0.8170, Val Loss: 1.1925, Val Accuracy: 0.7143
Epoch 6610/10000, Train Loss: 1.1046, Train Accuracy: 0.8103, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6611/10000, Train Loss: 1.0976, Train Accuracy: 0.8181, Val Loss: 1.1922, Val Accuracy: 0.7143
Epoch 6612/10000, Train Loss: 1.0884, Train Accuracy: 0.8281, Val Loss: 1.1923, Val Accuracy: 0.7188
Epoch 6613/10000, Train Loss: 1.0999, Train Accuracy: 0.8114, Val Loss: 1.1921, Val Accuracy: 0.7188
Epoch 6614/10000, Train Loss: 1.0987, Train Accuracy: 0.8103, Val Loss: 1.1917, Val Accuracy: 0.7143
Epoch 6615/10000, Train Loss: 1.1129, Train Accuracy: 0.8002, Val Loss: 1.1919, Val Accuracy: 0.7188
Epoch 6616/10000, Train Loss: 1.0975, Train Accuracy: 0.8170, Val Loss: 1.1919, Val Accuracy: 0.7188
Epoch 6617/10000, Train Loss: 1.1094, Train Accuracy: 0.8058, Val Loss: 1.1916, Val Accuracy: 0.7188
Epoch 6618/10000, Train Loss: 1.1058, Train Accuracy: 0.8103, Val Loss: 1.1917, Val Accuracy: 0.7188
Epoch 6619/10000, Train Loss: 1.1052, Train Accuracy: 0.8058, Val Loss: 1.1916, Val Accuracy: 0.7188
Epoch 6620/10000, Train Loss: 1.1027, Train Accuracy: 0.8080, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6621/10000, Train Loss: 1.0966, Train Accuracy: 0.8214, Val Loss: 1.1915, Val Accuracy: 0.7188
Epoch 6622/10000, Train Loss: 1.0969, Train Accuracy: 0.8181, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6623/10000, Train Loss: 1.0972, Train Accuracy: 0.8158, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6624/10000, Train Loss: 1.0926, Train Accuracy: 0.8248, Val Loss: 1.1915, Val Accuracy: 0.7188
Epoch 6625/10000, Train Loss: 1.0993, Train Accuracy: 0.8170, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6626/10000, Train Loss: 1.1017, Train Accuracy: 0.8125, Val Loss: 1.1915, Val Accuracy: 0.7188
Epoch 6627/10000, Train Loss: 1.1009, Train Accuracy: 0.8170, Val Loss: 1.1913, Val Accuracy: 0.7143
Epoch 6628/10000, Train Loss: 1.1012, Train Accuracy: 0.8103, Val Loss: 1.1914, Val Accuracy: 0.7143
Epoch 6629/10000, Train Loss: 1.0973, Train Accuracy: 0.8136, Val Loss: 1.1914, Val Accuracy: 0.7143
Epoch 6630/10000, Train Loss: 1.1001, Train Accuracy: 0.8092, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6631/10000, Train Loss: 1.0983, Train Accuracy: 0.8125, Val Loss: 1.1910, Val Accuracy: 0.7188
Epoch 6632/10000, Train Loss: 1.1096, Train Accuracy: 0.8002, Val Loss: 1.1913, Val Accuracy: 0.7188
Epoch 6633/10000, Train Loss: 1.0984, Train Accuracy: 0.8181, Val Loss: 1.1913, Val Accuracy: 0.7188
Epoch 6634/10000, Train Loss: 1.0939, Train Accuracy: 0.8170, Val Loss: 1.1914, Val Accuracy: 0.7188
Epoch 6635/10000, Train Loss: 1.1027, Train Accuracy: 0.8103, Val Loss: 1.1912, Val Accuracy: 0.7143
Epoch 6636/10000, Train Loss: 1.0938, Train Accuracy: 0.8259, Val Loss: 1.1911, Val Accuracy: 0.7188
Epoch 6637/10000, Train Loss: 1.0909, Train Accuracy: 0.8281, Val Loss: 1.1909, Val Accuracy: 0.7188
Epoch 6638/10000, Train Loss: 1.1106, Train Accuracy: 0.7980, Val Loss: 1.1910, Val Accuracy: 0.7188
Epoch 6639/10000, Train Loss: 1.1195, Train Accuracy: 0.7879, Val Loss: 1.1908, Val Accuracy: 0.7188
Epoch 6640/10000, Train Loss: 1.1011, Train Accuracy: 0.8114, Val Loss: 1.1909, Val Accuracy: 0.7188
Epoch 6641/10000, Train Loss: 1.1044, Train Accuracy: 0.8080, Val Loss: 1.1907, Val Accuracy: 0.7188
Epoch 6642/10000, Train Loss: 1.1167, Train Accuracy: 0.8002, Val Loss: 1.1905, Val Accuracy: 0.7188
Epoch 6643/10000, Train Loss: 1.0976, Train Accuracy: 0.8136, Val Loss: 1.1907, Val Accuracy: 0.7188
Epoch 6644/10000, Train Loss: 1.0929, Train Accuracy: 0.8192, Val Loss: 1.1905, Val Accuracy: 0.7188
Epoch 6645/10000, Train Loss: 1.0840, Train Accuracy: 0.8315, Val Loss: 1.1902, Val Accuracy: 0.7188
Epoch 6646/10000, Train Loss: 1.0959, Train Accuracy: 0.8214, Val Loss: 1.1903, Val Accuracy: 0.7188
Epoch 6647/10000, Train Loss: 1.1046, Train Accuracy: 0.8025, Val Loss: 1.1905, Val Accuracy: 0.7188
Epoch 6648/10000, Train Loss: 1.1026, Train Accuracy: 0.8192, Val Loss: 1.1906, Val Accuracy: 0.7188
Epoch 6649/10000, Train Loss: 1.0971, Train Accuracy: 0.8080, Val Loss: 1.1904, Val Accuracy: 0.7188
Epoch 6650/10000, Train Loss: 1.1098, Train Accuracy: 0.8025, Val Loss: 1.1904, Val Accuracy: 0.7188
Epoch 6651/10000, Train Loss: 1.0954, Train Accuracy: 0.8147, Val Loss: 1.1906, Val Accuracy: 0.7188
Epoch 6652/10000, Train Loss: 1.1056, Train Accuracy: 0.8058, Val Loss: 1.1906, Val Accuracy: 0.7188
Epoch 6653/10000, Train Loss: 1.0922, Train Accuracy: 0.8237, Val Loss: 1.1905, Val Accuracy: 0.7188
Epoch 6654/10000, Train Loss: 1.1017, Train Accuracy: 0.8170, Val Loss: 1.1902, Val Accuracy: 0.7188
Epoch 6655/10000, Train Loss: 1.0982, Train Accuracy: 0.8125, Val Loss: 1.1900, Val Accuracy: 0.7188
Epoch 6656/10000, Train Loss: 1.0844, Train Accuracy: 0.8281, Val Loss: 1.1904, Val Accuracy: 0.7188
Epoch 6657/10000, Train Loss: 1.1001, Train Accuracy: 0.8158, Val Loss: 1.1902, Val Accuracy: 0.7188
Epoch 6658/10000, Train Loss: 1.1027, Train Accuracy: 0.8080, Val Loss: 1.1901, Val Accuracy: 0.7188
Epoch 6659/10000, Train Loss: 1.1027, Train Accuracy: 0.8136, Val Loss: 1.1903, Val Accuracy: 0.7188
Epoch 6660/10000, Train Loss: 1.1140, Train Accuracy: 0.8025, Val Loss: 1.1904, Val Accuracy: 0.7188
Epoch 6661/10000, Train Loss: 1.1055, Train Accuracy: 0.8047, Val Loss: 1.1903, Val Accuracy: 0.7188
Epoch 6662/10000, Train Loss: 1.0936, Train Accuracy: 0.8214, Val Loss: 1.1903, Val Accuracy: 0.7188
Epoch 6663/10000, Train Loss: 1.0967, Train Accuracy: 0.8125, Val Loss: 1.1899, Val Accuracy: 0.7188
Epoch 6664/10000, Train Loss: 1.1016, Train Accuracy: 0.8103, Val Loss: 1.1899, Val Accuracy: 0.7188
Epoch 6665/10000, Train Loss: 1.0976, Train Accuracy: 0.8147, Val Loss: 1.1898, Val Accuracy: 0.7188
Epoch 6666/10000, Train Loss: 1.0909, Train Accuracy: 0.8237, Val Loss: 1.1899, Val Accuracy: 0.7188
Epoch 6667/10000, Train Loss: 1.0863, Train Accuracy: 0.8326, Val Loss: 1.1899, Val Accuracy: 0.7232
Epoch 6668/10000, Train Loss: 1.0990, Train Accuracy: 0.8158, Val Loss: 1.1899, Val Accuracy: 0.7188
Epoch 6669/10000, Train Loss: 1.1014, Train Accuracy: 0.8069, Val Loss: 1.1900, Val Accuracy: 0.7188
Epoch 6670/10000, Train Loss: 1.1023, Train Accuracy: 0.8092, Val Loss: 1.1902, Val Accuracy: 0.7188
Epoch 6671/10000, Train Loss: 1.0976, Train Accuracy: 0.8158, Val Loss: 1.1903, Val Accuracy: 0.7188
Epoch 6672/10000, Train Loss: 1.0933, Train Accuracy: 0.8214, Val Loss: 1.1904, Val Accuracy: 0.7188
Epoch 6673/10000, Train Loss: 1.1070, Train Accuracy: 0.8080, Val Loss: 1.1901, Val Accuracy: 0.7188
Epoch 6674/10000, Train Loss: 1.0922, Train Accuracy: 0.8181, Val Loss: 1.1900, Val Accuracy: 0.7188
Epoch 6675/10000, Train Loss: 1.1068, Train Accuracy: 0.8025, Val Loss: 1.1899, Val Accuracy: 0.7188
Epoch 6676/10000, Train Loss: 1.0949, Train Accuracy: 0.8147, Val Loss: 1.1897, Val Accuracy: 0.7188
Epoch 6677/10000, Train Loss: 1.1019, Train Accuracy: 0.8047, Val Loss: 1.1896, Val Accuracy: 0.7188
Epoch 6678/10000, Train Loss: 1.1087, Train Accuracy: 0.8025, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6679/10000, Train Loss: 1.0906, Train Accuracy: 0.8292, Val Loss: 1.1893, Val Accuracy: 0.7188
Epoch 6680/10000, Train Loss: 1.0987, Train Accuracy: 0.8158, Val Loss: 1.1888, Val Accuracy: 0.7188
Epoch 6681/10000, Train Loss: 1.1018, Train Accuracy: 0.8092, Val Loss: 1.1888, Val Accuracy: 0.7188
Epoch 6682/10000, Train Loss: 1.0993, Train Accuracy: 0.8103, Val Loss: 1.1889, Val Accuracy: 0.7188
Epoch 6683/10000, Train Loss: 1.1018, Train Accuracy: 0.8158, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6684/10000, Train Loss: 1.0943, Train Accuracy: 0.8248, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6685/10000, Train Loss: 1.1063, Train Accuracy: 0.8136, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6686/10000, Train Loss: 1.0964, Train Accuracy: 0.8214, Val Loss: 1.1894, Val Accuracy: 0.7232
Epoch 6687/10000, Train Loss: 1.0997, Train Accuracy: 0.8203, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6688/10000, Train Loss: 1.0958, Train Accuracy: 0.8248, Val Loss: 1.1895, Val Accuracy: 0.7232
Epoch 6689/10000, Train Loss: 1.1062, Train Accuracy: 0.8025, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6690/10000, Train Loss: 1.1135, Train Accuracy: 0.8013, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6691/10000, Train Loss: 1.0990, Train Accuracy: 0.8214, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6692/10000, Train Loss: 1.0972, Train Accuracy: 0.8158, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6693/10000, Train Loss: 1.1005, Train Accuracy: 0.8103, Val Loss: 1.1894, Val Accuracy: 0.7232
Epoch 6694/10000, Train Loss: 1.1011, Train Accuracy: 0.8058, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6695/10000, Train Loss: 1.1073, Train Accuracy: 0.8058, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6696/10000, Train Loss: 1.0958, Train Accuracy: 0.8214, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6697/10000, Train Loss: 1.1159, Train Accuracy: 0.7946, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6698/10000, Train Loss: 1.1055, Train Accuracy: 0.8080, Val Loss: 1.1890, Val Accuracy: 0.7188
Epoch 6699/10000, Train Loss: 1.1003, Train Accuracy: 0.8125, Val Loss: 1.1889, Val Accuracy: 0.7188
Epoch 6700/10000, Train Loss: 1.0880, Train Accuracy: 0.8259, Val Loss: 1.1886, Val Accuracy: 0.7188
Epoch 6701/10000, Train Loss: 1.0989, Train Accuracy: 0.8092, Val Loss: 1.1888, Val Accuracy: 0.7188
Epoch 6702/10000, Train Loss: 1.0995, Train Accuracy: 0.8181, Val Loss: 1.1889, Val Accuracy: 0.7188
Epoch 6703/10000, Train Loss: 1.1020, Train Accuracy: 0.8125, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6704/10000, Train Loss: 1.0922, Train Accuracy: 0.8203, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6705/10000, Train Loss: 1.1079, Train Accuracy: 0.8025, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6706/10000, Train Loss: 1.0963, Train Accuracy: 0.8114, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6707/10000, Train Loss: 1.0935, Train Accuracy: 0.8281, Val Loss: 1.1890, Val Accuracy: 0.7188
Epoch 6708/10000, Train Loss: 1.1000, Train Accuracy: 0.8192, Val Loss: 1.1891, Val Accuracy: 0.7188
Epoch 6709/10000, Train Loss: 1.0874, Train Accuracy: 0.8304, Val Loss: 1.1893, Val Accuracy: 0.7188
Epoch 6710/10000, Train Loss: 1.0926, Train Accuracy: 0.8225, Val Loss: 1.1891, Val Accuracy: 0.7188
Epoch 6711/10000, Train Loss: 1.1033, Train Accuracy: 0.8036, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6712/10000, Train Loss: 1.0971, Train Accuracy: 0.8170, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6713/10000, Train Loss: 1.0918, Train Accuracy: 0.8114, Val Loss: 1.1891, Val Accuracy: 0.7188
Epoch 6714/10000, Train Loss: 1.0953, Train Accuracy: 0.8125, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6715/10000, Train Loss: 1.0981, Train Accuracy: 0.8125, Val Loss: 1.1891, Val Accuracy: 0.7188
Epoch 6716/10000, Train Loss: 1.0901, Train Accuracy: 0.8292, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6717/10000, Train Loss: 1.1055, Train Accuracy: 0.8080, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6718/10000, Train Loss: 1.0993, Train Accuracy: 0.8181, Val Loss: 1.1893, Val Accuracy: 0.7188
Epoch 6719/10000, Train Loss: 1.0969, Train Accuracy: 0.8181, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6720/10000, Train Loss: 1.0994, Train Accuracy: 0.8203, Val Loss: 1.1888, Val Accuracy: 0.7188
Epoch 6721/10000, Train Loss: 1.1139, Train Accuracy: 0.7980, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6722/10000, Train Loss: 1.0972, Train Accuracy: 0.8125, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6723/10000, Train Loss: 1.0737, Train Accuracy: 0.8438, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6724/10000, Train Loss: 1.0821, Train Accuracy: 0.8371, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6725/10000, Train Loss: 1.1051, Train Accuracy: 0.8058, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6726/10000, Train Loss: 1.1054, Train Accuracy: 0.8080, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6727/10000, Train Loss: 1.0981, Train Accuracy: 0.8136, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6728/10000, Train Loss: 1.0835, Train Accuracy: 0.8348, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6729/10000, Train Loss: 1.0917, Train Accuracy: 0.8248, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6730/10000, Train Loss: 1.0865, Train Accuracy: 0.8292, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6731/10000, Train Loss: 1.0982, Train Accuracy: 0.8058, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6732/10000, Train Loss: 1.0976, Train Accuracy: 0.8158, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6733/10000, Train Loss: 1.1105, Train Accuracy: 0.8080, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6734/10000, Train Loss: 1.0899, Train Accuracy: 0.8214, Val Loss: 1.1884, Val Accuracy: 0.7232
Epoch 6735/10000, Train Loss: 1.0992, Train Accuracy: 0.8237, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6736/10000, Train Loss: 1.0735, Train Accuracy: 0.8460, Val Loss: 1.1884, Val Accuracy: 0.7232
Epoch 6737/10000, Train Loss: 1.0981, Train Accuracy: 0.8192, Val Loss: 1.1883, Val Accuracy: 0.7232
Epoch 6738/10000, Train Loss: 1.0947, Train Accuracy: 0.8237, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6739/10000, Train Loss: 1.0984, Train Accuracy: 0.8225, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6740/10000, Train Loss: 1.0926, Train Accuracy: 0.8270, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6741/10000, Train Loss: 1.0817, Train Accuracy: 0.8371, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6742/10000, Train Loss: 1.1069, Train Accuracy: 0.8092, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6743/10000, Train Loss: 1.1000, Train Accuracy: 0.8092, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6744/10000, Train Loss: 1.0929, Train Accuracy: 0.8192, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6745/10000, Train Loss: 1.1065, Train Accuracy: 0.8147, Val Loss: 1.1895, Val Accuracy: 0.7232
Epoch 6746/10000, Train Loss: 1.0957, Train Accuracy: 0.8259, Val Loss: 1.1895, Val Accuracy: 0.7232
Epoch 6747/10000, Train Loss: 1.1082, Train Accuracy: 0.8092, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6748/10000, Train Loss: 1.0792, Train Accuracy: 0.8393, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6749/10000, Train Loss: 1.1000, Train Accuracy: 0.8069, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6750/10000, Train Loss: 1.0971, Train Accuracy: 0.8147, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6751/10000, Train Loss: 1.0918, Train Accuracy: 0.8237, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6752/10000, Train Loss: 1.0902, Train Accuracy: 0.8270, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6753/10000, Train Loss: 1.0904, Train Accuracy: 0.8170, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6754/10000, Train Loss: 1.0995, Train Accuracy: 0.8103, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6755/10000, Train Loss: 1.1097, Train Accuracy: 0.8036, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6756/10000, Train Loss: 1.0967, Train Accuracy: 0.8114, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6757/10000, Train Loss: 1.1095, Train Accuracy: 0.8080, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6758/10000, Train Loss: 1.0982, Train Accuracy: 0.8192, Val Loss: 1.1888, Val Accuracy: 0.7232
Epoch 6759/10000, Train Loss: 1.0992, Train Accuracy: 0.8147, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6760/10000, Train Loss: 1.0786, Train Accuracy: 0.8415, Val Loss: 1.1884, Val Accuracy: 0.7232
Epoch 6761/10000, Train Loss: 1.0982, Train Accuracy: 0.8158, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6762/10000, Train Loss: 1.0957, Train Accuracy: 0.8158, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6763/10000, Train Loss: 1.1127, Train Accuracy: 0.8047, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6764/10000, Train Loss: 1.1031, Train Accuracy: 0.8058, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6765/10000, Train Loss: 1.0943, Train Accuracy: 0.8192, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6766/10000, Train Loss: 1.0789, Train Accuracy: 0.8404, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6767/10000, Train Loss: 1.1139, Train Accuracy: 0.7946, Val Loss: 1.1888, Val Accuracy: 0.7232
Epoch 6768/10000, Train Loss: 1.0904, Train Accuracy: 0.8248, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6769/10000, Train Loss: 1.1045, Train Accuracy: 0.8036, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6770/10000, Train Loss: 1.0911, Train Accuracy: 0.8225, Val Loss: 1.1888, Val Accuracy: 0.7232
Epoch 6771/10000, Train Loss: 1.1013, Train Accuracy: 0.8114, Val Loss: 1.1888, Val Accuracy: 0.7232
Epoch 6772/10000, Train Loss: 1.0984, Train Accuracy: 0.8192, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6773/10000, Train Loss: 1.1140, Train Accuracy: 0.8036, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6774/10000, Train Loss: 1.0916, Train Accuracy: 0.8248, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6775/10000, Train Loss: 1.0984, Train Accuracy: 0.8203, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6776/10000, Train Loss: 1.1052, Train Accuracy: 0.8092, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6777/10000, Train Loss: 1.0921, Train Accuracy: 0.8237, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6778/10000, Train Loss: 1.0901, Train Accuracy: 0.8248, Val Loss: 1.1894, Val Accuracy: 0.7232
Epoch 6779/10000, Train Loss: 1.0901, Train Accuracy: 0.8292, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6780/10000, Train Loss: 1.0823, Train Accuracy: 0.8326, Val Loss: 1.1893, Val Accuracy: 0.7232
Epoch 6781/10000, Train Loss: 1.0848, Train Accuracy: 0.8326, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6782/10000, Train Loss: 1.0823, Train Accuracy: 0.8359, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6783/10000, Train Loss: 1.0954, Train Accuracy: 0.8136, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6784/10000, Train Loss: 1.1063, Train Accuracy: 0.8092, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6785/10000, Train Loss: 1.0848, Train Accuracy: 0.8315, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6786/10000, Train Loss: 1.1077, Train Accuracy: 0.8103, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6787/10000, Train Loss: 1.1054, Train Accuracy: 0.8069, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6788/10000, Train Loss: 1.0824, Train Accuracy: 0.8304, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6789/10000, Train Loss: 1.0924, Train Accuracy: 0.8248, Val Loss: 1.1892, Val Accuracy: 0.7232
Epoch 6790/10000, Train Loss: 1.0990, Train Accuracy: 0.8170, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6791/10000, Train Loss: 1.0972, Train Accuracy: 0.8203, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6792/10000, Train Loss: 1.0851, Train Accuracy: 0.8315, Val Loss: 1.1890, Val Accuracy: 0.7232
Epoch 6793/10000, Train Loss: 1.0941, Train Accuracy: 0.8237, Val Loss: 1.1891, Val Accuracy: 0.7232
Epoch 6794/10000, Train Loss: 1.0990, Train Accuracy: 0.8114, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6795/10000, Train Loss: 1.0793, Train Accuracy: 0.8348, Val Loss: 1.1893, Val Accuracy: 0.7188
Epoch 6796/10000, Train Loss: 1.0896, Train Accuracy: 0.8225, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6797/10000, Train Loss: 1.0923, Train Accuracy: 0.8326, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6798/10000, Train Loss: 1.0946, Train Accuracy: 0.8203, Val Loss: 1.1895, Val Accuracy: 0.7188
Epoch 6799/10000, Train Loss: 1.0958, Train Accuracy: 0.8181, Val Loss: 1.1893, Val Accuracy: 0.7143
Epoch 6800/10000, Train Loss: 1.0945, Train Accuracy: 0.8114, Val Loss: 1.1891, Val Accuracy: 0.7143
Epoch 6801/10000, Train Loss: 1.0914, Train Accuracy: 0.8214, Val Loss: 1.1891, Val Accuracy: 0.7188
Epoch 6802/10000, Train Loss: 1.0898, Train Accuracy: 0.8248, Val Loss: 1.1892, Val Accuracy: 0.7188
Epoch 6803/10000, Train Loss: 1.1035, Train Accuracy: 0.8058, Val Loss: 1.1896, Val Accuracy: 0.7188
Epoch 6804/10000, Train Loss: 1.0979, Train Accuracy: 0.8147, Val Loss: 1.1896, Val Accuracy: 0.7098
Epoch 6805/10000, Train Loss: 1.1054, Train Accuracy: 0.8058, Val Loss: 1.1899, Val Accuracy: 0.7098
Epoch 6806/10000, Train Loss: 1.0897, Train Accuracy: 0.8304, Val Loss: 1.1896, Val Accuracy: 0.7098
Epoch 6807/10000, Train Loss: 1.0927, Train Accuracy: 0.8158, Val Loss: 1.1898, Val Accuracy: 0.7098
Epoch 6808/10000, Train Loss: 1.0899, Train Accuracy: 0.8214, Val Loss: 1.1898, Val Accuracy: 0.7098
Epoch 6809/10000, Train Loss: 1.1030, Train Accuracy: 0.8092, Val Loss: 1.1900, Val Accuracy: 0.7098
Epoch 6810/10000, Train Loss: 1.0932, Train Accuracy: 0.8203, Val Loss: 1.1896, Val Accuracy: 0.7098
Epoch 6811/10000, Train Loss: 1.0912, Train Accuracy: 0.8292, Val Loss: 1.1896, Val Accuracy: 0.7143
Epoch 6812/10000, Train Loss: 1.0869, Train Accuracy: 0.8304, Val Loss: 1.1898, Val Accuracy: 0.7098
Epoch 6813/10000, Train Loss: 1.1028, Train Accuracy: 0.8092, Val Loss: 1.1898, Val Accuracy: 0.7098
Epoch 6814/10000, Train Loss: 1.0851, Train Accuracy: 0.8382, Val Loss: 1.1898, Val Accuracy: 0.7098
Epoch 6815/10000, Train Loss: 1.0944, Train Accuracy: 0.8170, Val Loss: 1.1896, Val Accuracy: 0.7143
Epoch 6816/10000, Train Loss: 1.0925, Train Accuracy: 0.8225, Val Loss: 1.1892, Val Accuracy: 0.7143
Epoch 6817/10000, Train Loss: 1.0884, Train Accuracy: 0.8259, Val Loss: 1.1890, Val Accuracy: 0.7143
Epoch 6818/10000, Train Loss: 1.0921, Train Accuracy: 0.8203, Val Loss: 1.1890, Val Accuracy: 0.7098
Epoch 6819/10000, Train Loss: 1.0859, Train Accuracy: 0.8326, Val Loss: 1.1892, Val Accuracy: 0.7098
Epoch 6820/10000, Train Loss: 1.1060, Train Accuracy: 0.8047, Val Loss: 1.1894, Val Accuracy: 0.7098
Epoch 6821/10000, Train Loss: 1.0985, Train Accuracy: 0.8192, Val Loss: 1.1893, Val Accuracy: 0.7143
Epoch 6822/10000, Train Loss: 1.1085, Train Accuracy: 0.8058, Val Loss: 1.1891, Val Accuracy: 0.7098
Epoch 6823/10000, Train Loss: 1.0770, Train Accuracy: 0.8348, Val Loss: 1.1888, Val Accuracy: 0.7098
Epoch 6824/10000, Train Loss: 1.0988, Train Accuracy: 0.8114, Val Loss: 1.1888, Val Accuracy: 0.7098
Epoch 6825/10000, Train Loss: 1.0941, Train Accuracy: 0.8214, Val Loss: 1.1885, Val Accuracy: 0.7143
Epoch 6826/10000, Train Loss: 1.0963, Train Accuracy: 0.8203, Val Loss: 1.1884, Val Accuracy: 0.7143
Epoch 6827/10000, Train Loss: 1.0862, Train Accuracy: 0.8326, Val Loss: 1.1883, Val Accuracy: 0.7143
Epoch 6828/10000, Train Loss: 1.1055, Train Accuracy: 0.8002, Val Loss: 1.1886, Val Accuracy: 0.7188
Epoch 6829/10000, Train Loss: 1.0844, Train Accuracy: 0.8337, Val Loss: 1.1883, Val Accuracy: 0.7188
Epoch 6830/10000, Train Loss: 1.0901, Train Accuracy: 0.8237, Val Loss: 1.1885, Val Accuracy: 0.7143
Epoch 6831/10000, Train Loss: 1.0999, Train Accuracy: 0.8147, Val Loss: 1.1884, Val Accuracy: 0.7188
Epoch 6832/10000, Train Loss: 1.0836, Train Accuracy: 0.8292, Val Loss: 1.1884, Val Accuracy: 0.7232
Epoch 6833/10000, Train Loss: 1.0922, Train Accuracy: 0.8170, Val Loss: 1.1881, Val Accuracy: 0.7232
Epoch 6834/10000, Train Loss: 1.0991, Train Accuracy: 0.8136, Val Loss: 1.1884, Val Accuracy: 0.7321
Epoch 6835/10000, Train Loss: 1.0982, Train Accuracy: 0.8170, Val Loss: 1.1887, Val Accuracy: 0.7277
Epoch 6836/10000, Train Loss: 1.0998, Train Accuracy: 0.8158, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6837/10000, Train Loss: 1.0826, Train Accuracy: 0.8248, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6838/10000, Train Loss: 1.0932, Train Accuracy: 0.8259, Val Loss: 1.1889, Val Accuracy: 0.7232
Epoch 6839/10000, Train Loss: 1.0877, Train Accuracy: 0.8270, Val Loss: 1.1888, Val Accuracy: 0.7188
Epoch 6840/10000, Train Loss: 1.0842, Train Accuracy: 0.8225, Val Loss: 1.1886, Val Accuracy: 0.7143
Epoch 6841/10000, Train Loss: 1.0925, Train Accuracy: 0.8237, Val Loss: 1.1885, Val Accuracy: 0.7188
Epoch 6842/10000, Train Loss: 1.0898, Train Accuracy: 0.8237, Val Loss: 1.1886, Val Accuracy: 0.7188
Epoch 6843/10000, Train Loss: 1.1054, Train Accuracy: 0.8147, Val Loss: 1.1887, Val Accuracy: 0.7277
Epoch 6844/10000, Train Loss: 1.0985, Train Accuracy: 0.8103, Val Loss: 1.1889, Val Accuracy: 0.7277
Epoch 6845/10000, Train Loss: 1.0903, Train Accuracy: 0.8270, Val Loss: 1.1886, Val Accuracy: 0.7232
Epoch 6846/10000, Train Loss: 1.0755, Train Accuracy: 0.8460, Val Loss: 1.1885, Val Accuracy: 0.7277
Epoch 6847/10000, Train Loss: 1.0962, Train Accuracy: 0.8114, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6848/10000, Train Loss: 1.1034, Train Accuracy: 0.8092, Val Loss: 1.1886, Val Accuracy: 0.7277
Epoch 6849/10000, Train Loss: 1.0982, Train Accuracy: 0.8192, Val Loss: 1.1887, Val Accuracy: 0.7232
Epoch 6850/10000, Train Loss: 1.0840, Train Accuracy: 0.8326, Val Loss: 1.1885, Val Accuracy: 0.7232
Epoch 6851/10000, Train Loss: 1.0906, Train Accuracy: 0.8147, Val Loss: 1.1882, Val Accuracy: 0.7232
Epoch 6852/10000, Train Loss: 1.0966, Train Accuracy: 0.8147, Val Loss: 1.1881, Val Accuracy: 0.7188
Epoch 6853/10000, Train Loss: 1.0972, Train Accuracy: 0.8158, Val Loss: 1.1883, Val Accuracy: 0.7188
Epoch 6854/10000, Train Loss: 1.0917, Train Accuracy: 0.8270, Val Loss: 1.1882, Val Accuracy: 0.7143
Epoch 6855/10000, Train Loss: 1.1029, Train Accuracy: 0.8047, Val Loss: 1.1883, Val Accuracy: 0.7143
Epoch 6856/10000, Train Loss: 1.0817, Train Accuracy: 0.8348, Val Loss: 1.1881, Val Accuracy: 0.7143
Epoch 6857/10000, Train Loss: 1.0843, Train Accuracy: 0.8326, Val Loss: 1.1881, Val Accuracy: 0.7143
Epoch 6858/10000, Train Loss: 1.0781, Train Accuracy: 0.8415, Val Loss: 1.1880, Val Accuracy: 0.7143
Epoch 6859/10000, Train Loss: 1.0980, Train Accuracy: 0.8125, Val Loss: 1.1878, Val Accuracy: 0.7143
Epoch 6860/10000, Train Loss: 1.0985, Train Accuracy: 0.8181, Val Loss: 1.1878, Val Accuracy: 0.7188
Epoch 6861/10000, Train Loss: 1.0928, Train Accuracy: 0.8170, Val Loss: 1.1878, Val Accuracy: 0.7232
Epoch 6862/10000, Train Loss: 1.0917, Train Accuracy: 0.8214, Val Loss: 1.1879, Val Accuracy: 0.7232
Epoch 6863/10000, Train Loss: 1.0979, Train Accuracy: 0.8203, Val Loss: 1.1877, Val Accuracy: 0.7232
Epoch 6864/10000, Train Loss: 1.0896, Train Accuracy: 0.8170, Val Loss: 1.1878, Val Accuracy: 0.7232
Epoch 6865/10000, Train Loss: 1.1026, Train Accuracy: 0.8092, Val Loss: 1.1879, Val Accuracy: 0.7232
Epoch 6866/10000, Train Loss: 1.1049, Train Accuracy: 0.8158, Val Loss: 1.1877, Val Accuracy: 0.7188
Epoch 6867/10000, Train Loss: 1.1022, Train Accuracy: 0.8047, Val Loss: 1.1874, Val Accuracy: 0.7188
Epoch 6868/10000, Train Loss: 1.0875, Train Accuracy: 0.8203, Val Loss: 1.1874, Val Accuracy: 0.7188
Epoch 6869/10000, Train Loss: 1.0971, Train Accuracy: 0.8080, Val Loss: 1.1876, Val Accuracy: 0.7188
Epoch 6870/10000, Train Loss: 1.0937, Train Accuracy: 0.8248, Val Loss: 1.1879, Val Accuracy: 0.7188
Epoch 6871/10000, Train Loss: 1.1074, Train Accuracy: 0.7980, Val Loss: 1.1878, Val Accuracy: 0.7188
Epoch 6872/10000, Train Loss: 1.0973, Train Accuracy: 0.8147, Val Loss: 1.1875, Val Accuracy: 0.7188
Epoch 6873/10000, Train Loss: 1.0928, Train Accuracy: 0.8192, Val Loss: 1.1880, Val Accuracy: 0.7188
Epoch 6874/10000, Train Loss: 1.0802, Train Accuracy: 0.8326, Val Loss: 1.1881, Val Accuracy: 0.7143
Epoch 6875/10000, Train Loss: 1.1029, Train Accuracy: 0.8114, Val Loss: 1.1882, Val Accuracy: 0.7098
Epoch 6876/10000, Train Loss: 1.1028, Train Accuracy: 0.8080, Val Loss: 1.1880, Val Accuracy: 0.7098
Epoch 6877/10000, Train Loss: 1.0847, Train Accuracy: 0.8337, Val Loss: 1.1879, Val Accuracy: 0.7098
Epoch 6878/10000, Train Loss: 1.0971, Train Accuracy: 0.8158, Val Loss: 1.1880, Val Accuracy: 0.7143
Epoch 6879/10000, Train Loss: 1.0949, Train Accuracy: 0.8214, Val Loss: 1.1881, Val Accuracy: 0.7098
Epoch 6880/10000, Train Loss: 1.0982, Train Accuracy: 0.8158, Val Loss: 1.1882, Val Accuracy: 0.7098
Epoch 6881/10000, Train Loss: 1.0879, Train Accuracy: 0.8170, Val Loss: 1.1886, Val Accuracy: 0.7098
Epoch 6882/10000, Train Loss: 1.0994, Train Accuracy: 0.8103, Val Loss: 1.1884, Val Accuracy: 0.7098
Epoch 6883/10000, Train Loss: 1.0784, Train Accuracy: 0.8382, Val Loss: 1.1886, Val Accuracy: 0.7143
Epoch 6884/10000, Train Loss: 1.0871, Train Accuracy: 0.8315, Val Loss: 1.1885, Val Accuracy: 0.7143
Epoch 6885/10000, Train Loss: 1.1034, Train Accuracy: 0.8058, Val Loss: 1.1884, Val Accuracy: 0.7143
Epoch 6886/10000, Train Loss: 1.0802, Train Accuracy: 0.8371, Val Loss: 1.1882, Val Accuracy: 0.7188
Epoch 6887/10000, Train Loss: 1.1016, Train Accuracy: 0.8103, Val Loss: 1.1883, Val Accuracy: 0.7188
Epoch 6888/10000, Train Loss: 1.0812, Train Accuracy: 0.8326, Val Loss: 1.1882, Val Accuracy: 0.7143
Epoch 6889/10000, Train Loss: 1.0857, Train Accuracy: 0.8192, Val Loss: 1.1882, Val Accuracy: 0.7188
Epoch 6890/10000, Train Loss: 1.0903, Train Accuracy: 0.8270, Val Loss: 1.1883, Val Accuracy: 0.7188
Epoch 6891/10000, Train Loss: 1.0871, Train Accuracy: 0.8281, Val Loss: 1.1881, Val Accuracy: 0.7188
Epoch 6892/10000, Train Loss: 1.0948, Train Accuracy: 0.8103, Val Loss: 1.1877, Val Accuracy: 0.7188
Epoch 6893/10000, Train Loss: 1.0818, Train Accuracy: 0.8348, Val Loss: 1.1879, Val Accuracy: 0.7188
Epoch 6894/10000, Train Loss: 1.0943, Train Accuracy: 0.8214, Val Loss: 1.1879, Val Accuracy: 0.7188
Epoch 6895/10000, Train Loss: 1.0944, Train Accuracy: 0.8103, Val Loss: 1.1880, Val Accuracy: 0.7188
Epoch 6896/10000, Train Loss: 1.0931, Train Accuracy: 0.8259, Val Loss: 1.1877, Val Accuracy: 0.7188
Epoch 6897/10000, Train Loss: 1.0907, Train Accuracy: 0.8203, Val Loss: 1.1878, Val Accuracy: 0.7143
Epoch 6898/10000, Train Loss: 1.0875, Train Accuracy: 0.8225, Val Loss: 1.1880, Val Accuracy: 0.7188
Epoch 6899/10000, Train Loss: 1.0844, Train Accuracy: 0.8326, Val Loss: 1.1879, Val Accuracy: 0.7143
Epoch 6900/10000, Train Loss: 1.0890, Train Accuracy: 0.8237, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6901/10000, Train Loss: 1.0962, Train Accuracy: 0.8114, Val Loss: 1.1877, Val Accuracy: 0.7188
Epoch 6902/10000, Train Loss: 1.0899, Train Accuracy: 0.8270, Val Loss: 1.1881, Val Accuracy: 0.7188
Epoch 6903/10000, Train Loss: 1.0885, Train Accuracy: 0.8181, Val Loss: 1.1876, Val Accuracy: 0.7188
Epoch 6904/10000, Train Loss: 1.0885, Train Accuracy: 0.8192, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6905/10000, Train Loss: 1.0945, Train Accuracy: 0.8147, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6906/10000, Train Loss: 1.0975, Train Accuracy: 0.8147, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6907/10000, Train Loss: 1.0941, Train Accuracy: 0.8237, Val Loss: 1.1875, Val Accuracy: 0.7143
Epoch 6908/10000, Train Loss: 1.0924, Train Accuracy: 0.8181, Val Loss: 1.1875, Val Accuracy: 0.7143
Epoch 6909/10000, Train Loss: 1.0871, Train Accuracy: 0.8248, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6910/10000, Train Loss: 1.0894, Train Accuracy: 0.8292, Val Loss: 1.1876, Val Accuracy: 0.7143
Epoch 6911/10000, Train Loss: 1.0966, Train Accuracy: 0.8181, Val Loss: 1.1875, Val Accuracy: 0.7143
Epoch 6912/10000, Train Loss: 1.0865, Train Accuracy: 0.8225, Val Loss: 1.1875, Val Accuracy: 0.7188
Epoch 6913/10000, Train Loss: 1.0983, Train Accuracy: 0.8080, Val Loss: 1.1873, Val Accuracy: 0.7232
Epoch 6914/10000, Train Loss: 1.0896, Train Accuracy: 0.8136, Val Loss: 1.1874, Val Accuracy: 0.7188
Epoch 6915/10000, Train Loss: 1.0857, Train Accuracy: 0.8304, Val Loss: 1.1875, Val Accuracy: 0.7232
Epoch 6916/10000, Train Loss: 1.0893, Train Accuracy: 0.8214, Val Loss: 1.1873, Val Accuracy: 0.7232
Epoch 6917/10000, Train Loss: 1.0765, Train Accuracy: 0.8404, Val Loss: 1.1877, Val Accuracy: 0.7232
Epoch 6918/10000, Train Loss: 1.0916, Train Accuracy: 0.8158, Val Loss: 1.1875, Val Accuracy: 0.7232
Epoch 6919/10000, Train Loss: 1.0840, Train Accuracy: 0.8304, Val Loss: 1.1874, Val Accuracy: 0.7232
Epoch 6920/10000, Train Loss: 1.0967, Train Accuracy: 0.8147, Val Loss: 1.1870, Val Accuracy: 0.7188
Epoch 6921/10000, Train Loss: 1.0873, Train Accuracy: 0.8203, Val Loss: 1.1871, Val Accuracy: 0.7232
Epoch 6922/10000, Train Loss: 1.0822, Train Accuracy: 0.8315, Val Loss: 1.1872, Val Accuracy: 0.7277
Epoch 6923/10000, Train Loss: 1.0805, Train Accuracy: 0.8359, Val Loss: 1.1874, Val Accuracy: 0.7232
Epoch 6924/10000, Train Loss: 1.0972, Train Accuracy: 0.8114, Val Loss: 1.1874, Val Accuracy: 0.7232
Epoch 6925/10000, Train Loss: 1.0922, Train Accuracy: 0.8259, Val Loss: 1.1873, Val Accuracy: 0.7188
Epoch 6926/10000, Train Loss: 1.0898, Train Accuracy: 0.8248, Val Loss: 1.1874, Val Accuracy: 0.7188
Epoch 6927/10000, Train Loss: 1.0862, Train Accuracy: 0.8292, Val Loss: 1.1871, Val Accuracy: 0.7188
Epoch 6928/10000, Train Loss: 1.1098, Train Accuracy: 0.7991, Val Loss: 1.1872, Val Accuracy: 0.7188
Epoch 6929/10000, Train Loss: 1.0935, Train Accuracy: 0.8237, Val Loss: 1.1872, Val Accuracy: 0.7188
Epoch 6930/10000, Train Loss: 1.0881, Train Accuracy: 0.8315, Val Loss: 1.1873, Val Accuracy: 0.7188
Epoch 6931/10000, Train Loss: 1.0743, Train Accuracy: 0.8404, Val Loss: 1.1872, Val Accuracy: 0.7188
Epoch 6932/10000, Train Loss: 1.0874, Train Accuracy: 0.8225, Val Loss: 1.1869, Val Accuracy: 0.7188
Epoch 6933/10000, Train Loss: 1.0868, Train Accuracy: 0.8315, Val Loss: 1.1868, Val Accuracy: 0.7232
Epoch 6934/10000, Train Loss: 1.0865, Train Accuracy: 0.8292, Val Loss: 1.1869, Val Accuracy: 0.7188
Epoch 6935/10000, Train Loss: 1.0902, Train Accuracy: 0.8192, Val Loss: 1.1870, Val Accuracy: 0.7188
Epoch 6936/10000, Train Loss: 1.0866, Train Accuracy: 0.8248, Val Loss: 1.1872, Val Accuracy: 0.7188
Epoch 6937/10000, Train Loss: 1.0877, Train Accuracy: 0.8225, Val Loss: 1.1868, Val Accuracy: 0.7188
Epoch 6938/10000, Train Loss: 1.0945, Train Accuracy: 0.8158, Val Loss: 1.1869, Val Accuracy: 0.7188
Epoch 6939/10000, Train Loss: 1.0807, Train Accuracy: 0.8292, Val Loss: 1.1869, Val Accuracy: 0.7232
Epoch 6940/10000, Train Loss: 1.0839, Train Accuracy: 0.8348, Val Loss: 1.1871, Val Accuracy: 0.7232
Epoch 6941/10000, Train Loss: 1.0915, Train Accuracy: 0.8203, Val Loss: 1.1868, Val Accuracy: 0.7232
Epoch 6942/10000, Train Loss: 1.0891, Train Accuracy: 0.8248, Val Loss: 1.1868, Val Accuracy: 0.7232
Epoch 6943/10000, Train Loss: 1.0954, Train Accuracy: 0.8158, Val Loss: 1.1868, Val Accuracy: 0.7232
Epoch 6944/10000, Train Loss: 1.0916, Train Accuracy: 0.8225, Val Loss: 1.1867, Val Accuracy: 0.7232
Epoch 6945/10000, Train Loss: 1.0842, Train Accuracy: 0.8337, Val Loss: 1.1865, Val Accuracy: 0.7232
Epoch 6946/10000, Train Loss: 1.0867, Train Accuracy: 0.8337, Val Loss: 1.1864, Val Accuracy: 0.7232
Epoch 6947/10000, Train Loss: 1.0741, Train Accuracy: 0.8438, Val Loss: 1.1864, Val Accuracy: 0.7232
Epoch 6948/10000, Train Loss: 1.1027, Train Accuracy: 0.8136, Val Loss: 1.1865, Val Accuracy: 0.7232
Epoch 6949/10000, Train Loss: 1.0763, Train Accuracy: 0.8382, Val Loss: 1.1865, Val Accuracy: 0.7232
Epoch 6950/10000, Train Loss: 1.0832, Train Accuracy: 0.8371, Val Loss: 1.1867, Val Accuracy: 0.7232
Epoch 6951/10000, Train Loss: 1.0860, Train Accuracy: 0.8281, Val Loss: 1.1866, Val Accuracy: 0.7277
Epoch 6952/10000, Train Loss: 1.0877, Train Accuracy: 0.8181, Val Loss: 1.1860, Val Accuracy: 0.7188
Epoch 6953/10000, Train Loss: 1.0838, Train Accuracy: 0.8259, Val Loss: 1.1858, Val Accuracy: 0.7188
Epoch 6954/10000, Train Loss: 1.0850, Train Accuracy: 0.8270, Val Loss: 1.1860, Val Accuracy: 0.7188
Epoch 6955/10000, Train Loss: 1.0945, Train Accuracy: 0.8203, Val Loss: 1.1861, Val Accuracy: 0.7188
Epoch 6956/10000, Train Loss: 1.0921, Train Accuracy: 0.8237, Val Loss: 1.1860, Val Accuracy: 0.7188
Epoch 6957/10000, Train Loss: 1.0889, Train Accuracy: 0.8214, Val Loss: 1.1859, Val Accuracy: 0.7188
Epoch 6958/10000, Train Loss: 1.0862, Train Accuracy: 0.8348, Val Loss: 1.1861, Val Accuracy: 0.7188
Epoch 6959/10000, Train Loss: 1.0839, Train Accuracy: 0.8359, Val Loss: 1.1861, Val Accuracy: 0.7188
Epoch 6960/10000, Train Loss: 1.0829, Train Accuracy: 0.8248, Val Loss: 1.1864, Val Accuracy: 0.7188
Epoch 6961/10000, Train Loss: 1.0937, Train Accuracy: 0.8214, Val Loss: 1.1863, Val Accuracy: 0.7188
Epoch 6962/10000, Train Loss: 1.0887, Train Accuracy: 0.8248, Val Loss: 1.1863, Val Accuracy: 0.7188
Epoch 6963/10000, Train Loss: 1.0933, Train Accuracy: 0.8125, Val Loss: 1.1864, Val Accuracy: 0.7188
Epoch 6964/10000, Train Loss: 1.1113, Train Accuracy: 0.8047, Val Loss: 1.1862, Val Accuracy: 0.7188
Epoch 6965/10000, Train Loss: 1.0774, Train Accuracy: 0.8393, Val Loss: 1.1864, Val Accuracy: 0.7188
Epoch 6966/10000, Train Loss: 1.0819, Train Accuracy: 0.8382, Val Loss: 1.1863, Val Accuracy: 0.7188
Epoch 6967/10000, Train Loss: 1.1037, Train Accuracy: 0.8058, Val Loss: 1.1862, Val Accuracy: 0.7232
Epoch 6968/10000, Train Loss: 1.0966, Train Accuracy: 0.8136, Val Loss: 1.1863, Val Accuracy: 0.7188
Epoch 6969/10000, Train Loss: 1.0903, Train Accuracy: 0.8304, Val Loss: 1.1865, Val Accuracy: 0.7232
Epoch 6970/10000, Train Loss: 1.0937, Train Accuracy: 0.8225, Val Loss: 1.1865, Val Accuracy: 0.7232
Epoch 6971/10000, Train Loss: 1.0830, Train Accuracy: 0.8382, Val Loss: 1.1863, Val Accuracy: 0.7232
Epoch 6972/10000, Train Loss: 1.0890, Train Accuracy: 0.8237, Val Loss: 1.1861, Val Accuracy: 0.7232
Epoch 6973/10000, Train Loss: 1.0815, Train Accuracy: 0.8270, Val Loss: 1.1862, Val Accuracy: 0.7232
Epoch 6974/10000, Train Loss: 1.0883, Train Accuracy: 0.8225, Val Loss: 1.1862, Val Accuracy: 0.7277
Epoch 6975/10000, Train Loss: 1.0932, Train Accuracy: 0.8203, Val Loss: 1.1860, Val Accuracy: 0.7232
Epoch 6976/10000, Train Loss: 1.0891, Train Accuracy: 0.8170, Val Loss: 1.1861, Val Accuracy: 0.7232
Epoch 6977/10000, Train Loss: 1.0834, Train Accuracy: 0.8203, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 6978/10000, Train Loss: 1.0899, Train Accuracy: 0.8292, Val Loss: 1.1856, Val Accuracy: 0.7277
Epoch 6979/10000, Train Loss: 1.0996, Train Accuracy: 0.8214, Val Loss: 1.1857, Val Accuracy: 0.7277
Epoch 6980/10000, Train Loss: 1.0935, Train Accuracy: 0.8170, Val Loss: 1.1855, Val Accuracy: 0.7277
Epoch 6981/10000, Train Loss: 1.0879, Train Accuracy: 0.8348, Val Loss: 1.1855, Val Accuracy: 0.7321
Epoch 6982/10000, Train Loss: 1.0947, Train Accuracy: 0.8181, Val Loss: 1.1856, Val Accuracy: 0.7321
Epoch 6983/10000, Train Loss: 1.0893, Train Accuracy: 0.8225, Val Loss: 1.1855, Val Accuracy: 0.7321
Epoch 6984/10000, Train Loss: 1.0857, Train Accuracy: 0.8225, Val Loss: 1.1856, Val Accuracy: 0.7321
Epoch 6985/10000, Train Loss: 1.0902, Train Accuracy: 0.8281, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 6986/10000, Train Loss: 1.0858, Train Accuracy: 0.8337, Val Loss: 1.1860, Val Accuracy: 0.7188
Epoch 6987/10000, Train Loss: 1.0855, Train Accuracy: 0.8225, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 6988/10000, Train Loss: 1.0874, Train Accuracy: 0.8270, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 6989/10000, Train Loss: 1.1033, Train Accuracy: 0.8047, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 6990/10000, Train Loss: 1.0845, Train Accuracy: 0.8337, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 6991/10000, Train Loss: 1.0889, Train Accuracy: 0.8237, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 6992/10000, Train Loss: 1.0886, Train Accuracy: 0.8304, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 6993/10000, Train Loss: 1.0914, Train Accuracy: 0.8259, Val Loss: 1.1856, Val Accuracy: 0.7277
Epoch 6994/10000, Train Loss: 1.0922, Train Accuracy: 0.8136, Val Loss: 1.1856, Val Accuracy: 0.7277
Epoch 6995/10000, Train Loss: 1.0882, Train Accuracy: 0.8292, Val Loss: 1.1854, Val Accuracy: 0.7232
Epoch 6996/10000, Train Loss: 1.0834, Train Accuracy: 0.8259, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 6997/10000, Train Loss: 1.0887, Train Accuracy: 0.8214, Val Loss: 1.1853, Val Accuracy: 0.7188
Epoch 6998/10000, Train Loss: 1.0909, Train Accuracy: 0.8181, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 6999/10000, Train Loss: 1.0903, Train Accuracy: 0.8270, Val Loss: 1.1851, Val Accuracy: 0.7143
Epoch 7000/10000, Train Loss: 1.0894, Train Accuracy: 0.8259, Val Loss: 1.1852, Val Accuracy: 0.7143
Epoch 7001/10000, Train Loss: 1.0833, Train Accuracy: 0.8359, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7002/10000, Train Loss: 1.0959, Train Accuracy: 0.8158, Val Loss: 1.1852, Val Accuracy: 0.7143
Epoch 7003/10000, Train Loss: 1.0858, Train Accuracy: 0.8292, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7004/10000, Train Loss: 1.0778, Train Accuracy: 0.8304, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7005/10000, Train Loss: 1.0902, Train Accuracy: 0.8259, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7006/10000, Train Loss: 1.0824, Train Accuracy: 0.8237, Val Loss: 1.1848, Val Accuracy: 0.7188
Epoch 7007/10000, Train Loss: 1.0952, Train Accuracy: 0.8125, Val Loss: 1.1846, Val Accuracy: 0.7143
Epoch 7008/10000, Train Loss: 1.0745, Train Accuracy: 0.8382, Val Loss: 1.1847, Val Accuracy: 0.7188
Epoch 7009/10000, Train Loss: 1.0831, Train Accuracy: 0.8348, Val Loss: 1.1848, Val Accuracy: 0.7143
Epoch 7010/10000, Train Loss: 1.0933, Train Accuracy: 0.8103, Val Loss: 1.1849, Val Accuracy: 0.7143
Epoch 7011/10000, Train Loss: 1.0917, Train Accuracy: 0.8203, Val Loss: 1.1851, Val Accuracy: 0.7143
Epoch 7012/10000, Train Loss: 1.0889, Train Accuracy: 0.8192, Val Loss: 1.1853, Val Accuracy: 0.7188
Epoch 7013/10000, Train Loss: 1.0907, Train Accuracy: 0.8225, Val Loss: 1.1854, Val Accuracy: 0.7188
Epoch 7014/10000, Train Loss: 1.0807, Train Accuracy: 0.8337, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7015/10000, Train Loss: 1.0854, Train Accuracy: 0.8281, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7016/10000, Train Loss: 1.0825, Train Accuracy: 0.8359, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7017/10000, Train Loss: 1.0913, Train Accuracy: 0.8270, Val Loss: 1.1851, Val Accuracy: 0.7143
Epoch 7018/10000, Train Loss: 1.0841, Train Accuracy: 0.8359, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7019/10000, Train Loss: 1.0795, Train Accuracy: 0.8371, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7020/10000, Train Loss: 1.0891, Train Accuracy: 0.8203, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7021/10000, Train Loss: 1.0960, Train Accuracy: 0.8170, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7022/10000, Train Loss: 1.0940, Train Accuracy: 0.8136, Val Loss: 1.1855, Val Accuracy: 0.7143
Epoch 7023/10000, Train Loss: 1.0757, Train Accuracy: 0.8348, Val Loss: 1.1854, Val Accuracy: 0.7188
Epoch 7024/10000, Train Loss: 1.0826, Train Accuracy: 0.8304, Val Loss: 1.1853, Val Accuracy: 0.7277
Epoch 7025/10000, Train Loss: 1.0865, Train Accuracy: 0.8304, Val Loss: 1.1854, Val Accuracy: 0.7188
Epoch 7026/10000, Train Loss: 1.1007, Train Accuracy: 0.8047, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 7027/10000, Train Loss: 1.0800, Train Accuracy: 0.8348, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7028/10000, Train Loss: 1.0970, Train Accuracy: 0.8170, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7029/10000, Train Loss: 1.0676, Train Accuracy: 0.8549, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 7030/10000, Train Loss: 1.0864, Train Accuracy: 0.8304, Val Loss: 1.1852, Val Accuracy: 0.7143
Epoch 7031/10000, Train Loss: 1.0880, Train Accuracy: 0.8281, Val Loss: 1.1850, Val Accuracy: 0.7143
Epoch 7032/10000, Train Loss: 1.0857, Train Accuracy: 0.8393, Val Loss: 1.1850, Val Accuracy: 0.7188
Epoch 7033/10000, Train Loss: 1.0995, Train Accuracy: 0.8125, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7034/10000, Train Loss: 1.0880, Train Accuracy: 0.8225, Val Loss: 1.1851, Val Accuracy: 0.7277
Epoch 7035/10000, Train Loss: 1.0764, Train Accuracy: 0.8404, Val Loss: 1.1848, Val Accuracy: 0.7232
Epoch 7036/10000, Train Loss: 1.0923, Train Accuracy: 0.8214, Val Loss: 1.1850, Val Accuracy: 0.7277
Epoch 7037/10000, Train Loss: 1.0940, Train Accuracy: 0.8069, Val Loss: 1.1849, Val Accuracy: 0.7188
Epoch 7038/10000, Train Loss: 1.0983, Train Accuracy: 0.8103, Val Loss: 1.1850, Val Accuracy: 0.7232
Epoch 7039/10000, Train Loss: 1.0807, Train Accuracy: 0.8337, Val Loss: 1.1847, Val Accuracy: 0.7232
Epoch 7040/10000, Train Loss: 1.1005, Train Accuracy: 0.8114, Val Loss: 1.1847, Val Accuracy: 0.7232
Epoch 7041/10000, Train Loss: 1.0943, Train Accuracy: 0.8237, Val Loss: 1.1848, Val Accuracy: 0.7232
Epoch 7042/10000, Train Loss: 1.0746, Train Accuracy: 0.8404, Val Loss: 1.1848, Val Accuracy: 0.7232
Epoch 7043/10000, Train Loss: 1.0751, Train Accuracy: 0.8460, Val Loss: 1.1849, Val Accuracy: 0.7232
Epoch 7044/10000, Train Loss: 1.0973, Train Accuracy: 0.8214, Val Loss: 1.1849, Val Accuracy: 0.7188
Epoch 7045/10000, Train Loss: 1.0879, Train Accuracy: 0.8237, Val Loss: 1.1851, Val Accuracy: 0.7188
Epoch 7046/10000, Train Loss: 1.0888, Train Accuracy: 0.8259, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7047/10000, Train Loss: 1.0860, Train Accuracy: 0.8237, Val Loss: 1.1854, Val Accuracy: 0.7188
Epoch 7048/10000, Train Loss: 1.0750, Train Accuracy: 0.8426, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7049/10000, Train Loss: 1.0911, Train Accuracy: 0.8170, Val Loss: 1.1853, Val Accuracy: 0.7188
Epoch 7050/10000, Train Loss: 1.0852, Train Accuracy: 0.8281, Val Loss: 1.1853, Val Accuracy: 0.7188
Epoch 7051/10000, Train Loss: 1.0820, Train Accuracy: 0.8281, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 7052/10000, Train Loss: 1.0906, Train Accuracy: 0.8203, Val Loss: 1.1857, Val Accuracy: 0.7188
Epoch 7053/10000, Train Loss: 1.0900, Train Accuracy: 0.8237, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 7054/10000, Train Loss: 1.0893, Train Accuracy: 0.8270, Val Loss: 1.1854, Val Accuracy: 0.7232
Epoch 7055/10000, Train Loss: 1.0836, Train Accuracy: 0.8348, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7056/10000, Train Loss: 1.0837, Train Accuracy: 0.8337, Val Loss: 1.1852, Val Accuracy: 0.7188
Epoch 7057/10000, Train Loss: 1.0867, Train Accuracy: 0.8237, Val Loss: 1.1857, Val Accuracy: 0.7188
Epoch 7058/10000, Train Loss: 1.0696, Train Accuracy: 0.8449, Val Loss: 1.1858, Val Accuracy: 0.7232
Epoch 7059/10000, Train Loss: 1.0899, Train Accuracy: 0.8203, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 7060/10000, Train Loss: 1.0784, Train Accuracy: 0.8337, Val Loss: 1.1858, Val Accuracy: 0.7232
Epoch 7061/10000, Train Loss: 1.0691, Train Accuracy: 0.8438, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 7062/10000, Train Loss: 1.0911, Train Accuracy: 0.8237, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 7063/10000, Train Loss: 1.0799, Train Accuracy: 0.8304, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 7064/10000, Train Loss: 1.0806, Train Accuracy: 0.8404, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 7065/10000, Train Loss: 1.0833, Train Accuracy: 0.8214, Val Loss: 1.1858, Val Accuracy: 0.7232
Epoch 7066/10000, Train Loss: 1.0972, Train Accuracy: 0.8203, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 7067/10000, Train Loss: 1.0949, Train Accuracy: 0.8225, Val Loss: 1.1861, Val Accuracy: 0.7188
Epoch 7068/10000, Train Loss: 1.0941, Train Accuracy: 0.8237, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 7069/10000, Train Loss: 1.0976, Train Accuracy: 0.8147, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 7070/10000, Train Loss: 1.1119, Train Accuracy: 0.8002, Val Loss: 1.1860, Val Accuracy: 0.7188
Epoch 7071/10000, Train Loss: 1.0801, Train Accuracy: 0.8326, Val Loss: 1.1857, Val Accuracy: 0.7188
Epoch 7072/10000, Train Loss: 1.0858, Train Accuracy: 0.8237, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7073/10000, Train Loss: 1.0731, Train Accuracy: 0.8460, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7074/10000, Train Loss: 1.0876, Train Accuracy: 0.8259, Val Loss: 1.1855, Val Accuracy: 0.7188
Epoch 7075/10000, Train Loss: 1.0767, Train Accuracy: 0.8415, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 7076/10000, Train Loss: 1.0895, Train Accuracy: 0.8214, Val Loss: 1.1857, Val Accuracy: 0.7188
Epoch 7077/10000, Train Loss: 1.0901, Train Accuracy: 0.8203, Val Loss: 1.1853, Val Accuracy: 0.7188
Epoch 7078/10000, Train Loss: 1.0932, Train Accuracy: 0.8192, Val Loss: 1.1856, Val Accuracy: 0.7188
Epoch 7079/10000, Train Loss: 1.0752, Train Accuracy: 0.8393, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 7080/10000, Train Loss: 1.1000, Train Accuracy: 0.8103, Val Loss: 1.1858, Val Accuracy: 0.7188
Epoch 7081/10000, Train Loss: 1.0832, Train Accuracy: 0.8337, Val Loss: 1.1861, Val Accuracy: 0.7232
Epoch 7082/10000, Train Loss: 1.0744, Train Accuracy: 0.8348, Val Loss: 1.1858, Val Accuracy: 0.7188
Epoch 7083/10000, Train Loss: 1.0695, Train Accuracy: 0.8493, Val Loss: 1.1858, Val Accuracy: 0.7188
Epoch 7084/10000, Train Loss: 1.0939, Train Accuracy: 0.8181, Val Loss: 1.1857, Val Accuracy: 0.7188
Epoch 7085/10000, Train Loss: 1.0883, Train Accuracy: 0.8225, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 7086/10000, Train Loss: 1.0817, Train Accuracy: 0.8281, Val Loss: 1.1860, Val Accuracy: 0.7277
Epoch 7087/10000, Train Loss: 1.0830, Train Accuracy: 0.8292, Val Loss: 1.1859, Val Accuracy: 0.7277
Epoch 7088/10000, Train Loss: 1.0964, Train Accuracy: 0.8170, Val Loss: 1.1858, Val Accuracy: 0.7232
Epoch 7089/10000, Train Loss: 1.0873, Train Accuracy: 0.8292, Val Loss: 1.1860, Val Accuracy: 0.7232
Epoch 7090/10000, Train Loss: 1.0875, Train Accuracy: 0.8292, Val Loss: 1.1859, Val Accuracy: 0.7232
Epoch 7091/10000, Train Loss: 1.0980, Train Accuracy: 0.8170, Val Loss: 1.1860, Val Accuracy: 0.7232
Epoch 7092/10000, Train Loss: 1.0778, Train Accuracy: 0.8415, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 7093/10000, Train Loss: 1.0900, Train Accuracy: 0.8259, Val Loss: 1.1858, Val Accuracy: 0.7232
Epoch 7094/10000, Train Loss: 1.0730, Train Accuracy: 0.8426, Val Loss: 1.1857, Val Accuracy: 0.7232
Epoch 7095/10000, Train Loss: 1.0771, Train Accuracy: 0.8359, Val Loss: 1.1854, Val Accuracy: 0.7232
Epoch 7096/10000, Train Loss: 1.0850, Train Accuracy: 0.8225, Val Loss: 1.1856, Val Accuracy: 0.7277
Epoch 7097/10000, Train Loss: 1.0842, Train Accuracy: 0.8315, Val Loss: 1.1855, Val Accuracy: 0.7232
Epoch 7098/10000, Train Loss: 1.0765, Train Accuracy: 0.8404, Val Loss: 1.1851, Val Accuracy: 0.7232
Epoch 7099/10000, Train Loss: 1.0880, Train Accuracy: 0.8248, Val Loss: 1.1853, Val Accuracy: 0.7277
Epoch 7100/10000, Train Loss: 1.0729, Train Accuracy: 0.8426, Val Loss: 1.1851, Val Accuracy: 0.7321
Epoch 7101/10000, Train Loss: 1.0824, Train Accuracy: 0.8237, Val Loss: 1.1850, Val Accuracy: 0.7321
Epoch 7102/10000, Train Loss: 1.0811, Train Accuracy: 0.8359, Val Loss: 1.1850, Val Accuracy: 0.7277
Epoch 7103/10000, Train Loss: 1.0742, Train Accuracy: 0.8404, Val Loss: 1.1851, Val Accuracy: 0.7321
Epoch 7104/10000, Train Loss: 1.0671, Train Accuracy: 0.8516, Val Loss: 1.1853, Val Accuracy: 0.7321
Epoch 7105/10000, Train Loss: 1.0974, Train Accuracy: 0.8125, Val Loss: 1.1854, Val Accuracy: 0.7277
Epoch 7106/10000, Train Loss: 1.0889, Train Accuracy: 0.8259, Val Loss: 1.1857, Val Accuracy: 0.7277
Epoch 7107/10000, Train Loss: 1.0844, Train Accuracy: 0.8292, Val Loss: 1.1856, Val Accuracy: 0.7277
Epoch 7108/10000, Train Loss: 1.0780, Train Accuracy: 0.8326, Val Loss: 1.1853, Val Accuracy: 0.7277
Epoch 7109/10000, Train Loss: 1.0832, Train Accuracy: 0.8348, Val Loss: 1.1850, Val Accuracy: 0.7232
Epoch 7110/10000, Train Loss: 1.0781, Train Accuracy: 0.8382, Val Loss: 1.1848, Val Accuracy: 0.7232
Epoch 7111/10000, Train Loss: 1.0829, Train Accuracy: 0.8270, Val Loss: 1.1847, Val Accuracy: 0.7277
Epoch 7112/10000, Train Loss: 1.0770, Train Accuracy: 0.8382, Val Loss: 1.1843, Val Accuracy: 0.7321
Epoch 7113/10000, Train Loss: 1.1030, Train Accuracy: 0.8103, Val Loss: 1.1844, Val Accuracy: 0.7321
Epoch 7114/10000, Train Loss: 1.0746, Train Accuracy: 0.8404, Val Loss: 1.1845, Val Accuracy: 0.7277
Epoch 7115/10000, Train Loss: 1.0701, Train Accuracy: 0.8371, Val Loss: 1.1841, Val Accuracy: 0.7277
Epoch 7116/10000, Train Loss: 1.0871, Train Accuracy: 0.8237, Val Loss: 1.1844, Val Accuracy: 0.7277
Epoch 7117/10000, Train Loss: 1.0896, Train Accuracy: 0.8237, Val Loss: 1.1842, Val Accuracy: 0.7232
Epoch 7118/10000, Train Loss: 1.0794, Train Accuracy: 0.8382, Val Loss: 1.1842, Val Accuracy: 0.7277
Epoch 7119/10000, Train Loss: 1.0896, Train Accuracy: 0.8237, Val Loss: 1.1842, Val Accuracy: 0.7232
Epoch 7120/10000, Train Loss: 1.0842, Train Accuracy: 0.8315, Val Loss: 1.1844, Val Accuracy: 0.7232
Epoch 7121/10000, Train Loss: 1.0969, Train Accuracy: 0.8136, Val Loss: 1.1844, Val Accuracy: 0.7232
Epoch 7122/10000, Train Loss: 1.0779, Train Accuracy: 0.8359, Val Loss: 1.1842, Val Accuracy: 0.7277
Epoch 7123/10000, Train Loss: 1.0720, Train Accuracy: 0.8493, Val Loss: 1.1845, Val Accuracy: 0.7277
Epoch 7124/10000, Train Loss: 1.0843, Train Accuracy: 0.8371, Val Loss: 1.1846, Val Accuracy: 0.7321
Epoch 7125/10000, Train Loss: 1.0742, Train Accuracy: 0.8371, Val Loss: 1.1847, Val Accuracy: 0.7277
Epoch 7126/10000, Train Loss: 1.0867, Train Accuracy: 0.8270, Val Loss: 1.1847, Val Accuracy: 0.7277
Epoch 7127/10000, Train Loss: 1.0849, Train Accuracy: 0.8270, Val Loss: 1.1846, Val Accuracy: 0.7277
Epoch 7128/10000, Train Loss: 1.0842, Train Accuracy: 0.8248, Val Loss: 1.1845, Val Accuracy: 0.7321
Epoch 7129/10000, Train Loss: 1.0954, Train Accuracy: 0.8192, Val Loss: 1.1846, Val Accuracy: 0.7321
Epoch 7130/10000, Train Loss: 1.0902, Train Accuracy: 0.8203, Val Loss: 1.1845, Val Accuracy: 0.7321
Epoch 7131/10000, Train Loss: 1.0888, Train Accuracy: 0.8158, Val Loss: 1.1845, Val Accuracy: 0.7321
Epoch 7132/10000, Train Loss: 1.0846, Train Accuracy: 0.8259, Val Loss: 1.1847, Val Accuracy: 0.7321
Epoch 7133/10000, Train Loss: 1.0843, Train Accuracy: 0.8304, Val Loss: 1.1844, Val Accuracy: 0.7321
Epoch 7134/10000, Train Loss: 1.0842, Train Accuracy: 0.8270, Val Loss: 1.1845, Val Accuracy: 0.7321
Epoch 7135/10000, Train Loss: 1.0787, Train Accuracy: 0.8292, Val Loss: 1.1842, Val Accuracy: 0.7321
Epoch 7136/10000, Train Loss: 1.0914, Train Accuracy: 0.8248, Val Loss: 1.1841, Val Accuracy: 0.7321
Epoch 7137/10000, Train Loss: 1.0913, Train Accuracy: 0.8147, Val Loss: 1.1842, Val Accuracy: 0.7277
Epoch 7138/10000, Train Loss: 1.0841, Train Accuracy: 0.8393, Val Loss: 1.1841, Val Accuracy: 0.7321
Epoch 7139/10000, Train Loss: 1.0928, Train Accuracy: 0.8192, Val Loss: 1.1838, Val Accuracy: 0.7366
Epoch 7140/10000, Train Loss: 1.0860, Train Accuracy: 0.8259, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7141/10000, Train Loss: 1.0925, Train Accuracy: 0.8103, Val Loss: 1.1837, Val Accuracy: 0.7321
Epoch 7142/10000, Train Loss: 1.0801, Train Accuracy: 0.8326, Val Loss: 1.1838, Val Accuracy: 0.7321
Epoch 7143/10000, Train Loss: 1.0883, Train Accuracy: 0.8270, Val Loss: 1.1837, Val Accuracy: 0.7277
Epoch 7144/10000, Train Loss: 1.0945, Train Accuracy: 0.8170, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7145/10000, Train Loss: 1.0928, Train Accuracy: 0.8203, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7146/10000, Train Loss: 1.0936, Train Accuracy: 0.8181, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7147/10000, Train Loss: 1.0849, Train Accuracy: 0.8270, Val Loss: 1.1836, Val Accuracy: 0.7321
Epoch 7148/10000, Train Loss: 1.0831, Train Accuracy: 0.8326, Val Loss: 1.1837, Val Accuracy: 0.7321
Epoch 7149/10000, Train Loss: 1.0808, Train Accuracy: 0.8438, Val Loss: 1.1838, Val Accuracy: 0.7321
Epoch 7150/10000, Train Loss: 1.0825, Train Accuracy: 0.8382, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7151/10000, Train Loss: 1.0913, Train Accuracy: 0.8259, Val Loss: 1.1833, Val Accuracy: 0.7321
Epoch 7152/10000, Train Loss: 1.0866, Train Accuracy: 0.8270, Val Loss: 1.1835, Val Accuracy: 0.7321
Epoch 7153/10000, Train Loss: 1.0661, Train Accuracy: 0.8493, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7154/10000, Train Loss: 1.0781, Train Accuracy: 0.8326, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7155/10000, Train Loss: 1.0775, Train Accuracy: 0.8393, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7156/10000, Train Loss: 1.0938, Train Accuracy: 0.8181, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7157/10000, Train Loss: 1.1017, Train Accuracy: 0.8047, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7158/10000, Train Loss: 1.0812, Train Accuracy: 0.8337, Val Loss: 1.1835, Val Accuracy: 0.7321
Epoch 7159/10000, Train Loss: 1.0677, Train Accuracy: 0.8449, Val Loss: 1.1837, Val Accuracy: 0.7321
Epoch 7160/10000, Train Loss: 1.0822, Train Accuracy: 0.8326, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7161/10000, Train Loss: 1.0936, Train Accuracy: 0.8158, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7162/10000, Train Loss: 1.0918, Train Accuracy: 0.8214, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7163/10000, Train Loss: 1.0847, Train Accuracy: 0.8304, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7164/10000, Train Loss: 1.0820, Train Accuracy: 0.8359, Val Loss: 1.1835, Val Accuracy: 0.7321
Epoch 7165/10000, Train Loss: 1.0882, Train Accuracy: 0.8281, Val Loss: 1.1832, Val Accuracy: 0.7321
Epoch 7166/10000, Train Loss: 1.0814, Train Accuracy: 0.8248, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7167/10000, Train Loss: 1.0837, Train Accuracy: 0.8326, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7168/10000, Train Loss: 1.0863, Train Accuracy: 0.8281, Val Loss: 1.1828, Val Accuracy: 0.7321
Epoch 7169/10000, Train Loss: 1.0916, Train Accuracy: 0.8237, Val Loss: 1.1827, Val Accuracy: 0.7366
Epoch 7170/10000, Train Loss: 1.0855, Train Accuracy: 0.8281, Val Loss: 1.1829, Val Accuracy: 0.7366
Epoch 7171/10000, Train Loss: 1.0803, Train Accuracy: 0.8281, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7172/10000, Train Loss: 1.0757, Train Accuracy: 0.8393, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7173/10000, Train Loss: 1.0848, Train Accuracy: 0.8248, Val Loss: 1.1828, Val Accuracy: 0.7321
Epoch 7174/10000, Train Loss: 1.0845, Train Accuracy: 0.8214, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7175/10000, Train Loss: 1.0821, Train Accuracy: 0.8259, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7176/10000, Train Loss: 1.0716, Train Accuracy: 0.8382, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7177/10000, Train Loss: 1.0782, Train Accuracy: 0.8371, Val Loss: 1.1831, Val Accuracy: 0.7366
Epoch 7178/10000, Train Loss: 1.0887, Train Accuracy: 0.8203, Val Loss: 1.1830, Val Accuracy: 0.7366
Epoch 7179/10000, Train Loss: 1.0788, Train Accuracy: 0.8315, Val Loss: 1.1830, Val Accuracy: 0.7366
Epoch 7180/10000, Train Loss: 1.0890, Train Accuracy: 0.8181, Val Loss: 1.1833, Val Accuracy: 0.7366
Epoch 7181/10000, Train Loss: 1.0724, Train Accuracy: 0.8471, Val Loss: 1.1834, Val Accuracy: 0.7366
Epoch 7182/10000, Train Loss: 1.0795, Train Accuracy: 0.8371, Val Loss: 1.1832, Val Accuracy: 0.7366
Epoch 7183/10000, Train Loss: 1.0803, Train Accuracy: 0.8326, Val Loss: 1.1828, Val Accuracy: 0.7366
Epoch 7184/10000, Train Loss: 1.0903, Train Accuracy: 0.8237, Val Loss: 1.1823, Val Accuracy: 0.7366
Epoch 7185/10000, Train Loss: 1.0814, Train Accuracy: 0.8259, Val Loss: 1.1825, Val Accuracy: 0.7366
Epoch 7186/10000, Train Loss: 1.0858, Train Accuracy: 0.8270, Val Loss: 1.1824, Val Accuracy: 0.7366
Epoch 7187/10000, Train Loss: 1.0750, Train Accuracy: 0.8382, Val Loss: 1.1824, Val Accuracy: 0.7366
Epoch 7188/10000, Train Loss: 1.0767, Train Accuracy: 0.8415, Val Loss: 1.1825, Val Accuracy: 0.7366
Epoch 7189/10000, Train Loss: 1.0844, Train Accuracy: 0.8281, Val Loss: 1.1826, Val Accuracy: 0.7366
Epoch 7190/10000, Train Loss: 1.0838, Train Accuracy: 0.8259, Val Loss: 1.1825, Val Accuracy: 0.7366
Epoch 7191/10000, Train Loss: 1.0797, Train Accuracy: 0.8304, Val Loss: 1.1828, Val Accuracy: 0.7321
Epoch 7192/10000, Train Loss: 1.0904, Train Accuracy: 0.8237, Val Loss: 1.1826, Val Accuracy: 0.7366
Epoch 7193/10000, Train Loss: 1.0699, Train Accuracy: 0.8460, Val Loss: 1.1827, Val Accuracy: 0.7366
Epoch 7194/10000, Train Loss: 1.0743, Train Accuracy: 0.8393, Val Loss: 1.1825, Val Accuracy: 0.7366
Epoch 7195/10000, Train Loss: 1.0876, Train Accuracy: 0.8248, Val Loss: 1.1824, Val Accuracy: 0.7366
Epoch 7196/10000, Train Loss: 1.0847, Train Accuracy: 0.8326, Val Loss: 1.1826, Val Accuracy: 0.7366
Epoch 7197/10000, Train Loss: 1.0879, Train Accuracy: 0.8270, Val Loss: 1.1827, Val Accuracy: 0.7366
Epoch 7198/10000, Train Loss: 1.0873, Train Accuracy: 0.8237, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7199/10000, Train Loss: 1.0683, Train Accuracy: 0.8460, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7200/10000, Train Loss: 1.0768, Train Accuracy: 0.8393, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7201/10000, Train Loss: 1.0683, Train Accuracy: 0.8516, Val Loss: 1.1822, Val Accuracy: 0.7321
Epoch 7202/10000, Train Loss: 1.0823, Train Accuracy: 0.8304, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7203/10000, Train Loss: 1.0992, Train Accuracy: 0.8080, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7204/10000, Train Loss: 1.0848, Train Accuracy: 0.8326, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7205/10000, Train Loss: 1.0767, Train Accuracy: 0.8404, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7206/10000, Train Loss: 1.0763, Train Accuracy: 0.8337, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7207/10000, Train Loss: 1.0802, Train Accuracy: 0.8359, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7208/10000, Train Loss: 1.0840, Train Accuracy: 0.8270, Val Loss: 1.1818, Val Accuracy: 0.7321
Epoch 7209/10000, Train Loss: 1.0824, Train Accuracy: 0.8270, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7210/10000, Train Loss: 1.0776, Train Accuracy: 0.8426, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7211/10000, Train Loss: 1.0832, Train Accuracy: 0.8225, Val Loss: 1.1822, Val Accuracy: 0.7321
Epoch 7212/10000, Train Loss: 1.0747, Train Accuracy: 0.8482, Val Loss: 1.1823, Val Accuracy: 0.7321
Epoch 7213/10000, Train Loss: 1.0805, Train Accuracy: 0.8259, Val Loss: 1.1823, Val Accuracy: 0.7321
Epoch 7214/10000, Train Loss: 1.0860, Train Accuracy: 0.8248, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7215/10000, Train Loss: 1.0822, Train Accuracy: 0.8292, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7216/10000, Train Loss: 1.0726, Train Accuracy: 0.8382, Val Loss: 1.1826, Val Accuracy: 0.7366
Epoch 7217/10000, Train Loss: 1.0881, Train Accuracy: 0.8214, Val Loss: 1.1826, Val Accuracy: 0.7366
Epoch 7218/10000, Train Loss: 1.0856, Train Accuracy: 0.8304, Val Loss: 1.1825, Val Accuracy: 0.7366
Epoch 7219/10000, Train Loss: 1.0685, Train Accuracy: 0.8404, Val Loss: 1.1827, Val Accuracy: 0.7366
Epoch 7220/10000, Train Loss: 1.0801, Train Accuracy: 0.8326, Val Loss: 1.1826, Val Accuracy: 0.7321
Epoch 7221/10000, Train Loss: 1.0836, Train Accuracy: 0.8337, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7222/10000, Train Loss: 1.0937, Train Accuracy: 0.8147, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7223/10000, Train Loss: 1.0723, Train Accuracy: 0.8393, Val Loss: 1.1828, Val Accuracy: 0.7321
Epoch 7224/10000, Train Loss: 1.0742, Train Accuracy: 0.8382, Val Loss: 1.1824, Val Accuracy: 0.7321
Epoch 7225/10000, Train Loss: 1.0839, Train Accuracy: 0.8225, Val Loss: 1.1824, Val Accuracy: 0.7321
Epoch 7226/10000, Train Loss: 1.0890, Train Accuracy: 0.8248, Val Loss: 1.1822, Val Accuracy: 0.7321
Epoch 7227/10000, Train Loss: 1.0861, Train Accuracy: 0.8304, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7228/10000, Train Loss: 1.0851, Train Accuracy: 0.8371, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7229/10000, Train Loss: 1.0843, Train Accuracy: 0.8281, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7230/10000, Train Loss: 1.0808, Train Accuracy: 0.8426, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7231/10000, Train Loss: 1.0940, Train Accuracy: 0.8237, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7232/10000, Train Loss: 1.0870, Train Accuracy: 0.8270, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7233/10000, Train Loss: 1.0773, Train Accuracy: 0.8337, Val Loss: 1.1822, Val Accuracy: 0.7366
Epoch 7234/10000, Train Loss: 1.0638, Train Accuracy: 0.8516, Val Loss: 1.1819, Val Accuracy: 0.7366
Epoch 7235/10000, Train Loss: 1.0778, Train Accuracy: 0.8382, Val Loss: 1.1819, Val Accuracy: 0.7366
Epoch 7236/10000, Train Loss: 1.0769, Train Accuracy: 0.8337, Val Loss: 1.1820, Val Accuracy: 0.7366
Epoch 7237/10000, Train Loss: 1.0855, Train Accuracy: 0.8281, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7238/10000, Train Loss: 1.0873, Train Accuracy: 0.8304, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7239/10000, Train Loss: 1.0822, Train Accuracy: 0.8304, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7240/10000, Train Loss: 1.0719, Train Accuracy: 0.8382, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7241/10000, Train Loss: 1.0789, Train Accuracy: 0.8393, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7242/10000, Train Loss: 1.0817, Train Accuracy: 0.8315, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7243/10000, Train Loss: 1.0799, Train Accuracy: 0.8326, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7244/10000, Train Loss: 1.0966, Train Accuracy: 0.8136, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7245/10000, Train Loss: 1.0780, Train Accuracy: 0.8304, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7246/10000, Train Loss: 1.0769, Train Accuracy: 0.8359, Val Loss: 1.1818, Val Accuracy: 0.7321
Epoch 7247/10000, Train Loss: 1.0828, Train Accuracy: 0.8292, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7248/10000, Train Loss: 1.0841, Train Accuracy: 0.8292, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7249/10000, Train Loss: 1.0756, Train Accuracy: 0.8438, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7250/10000, Train Loss: 1.0714, Train Accuracy: 0.8504, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7251/10000, Train Loss: 1.0805, Train Accuracy: 0.8371, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7252/10000, Train Loss: 1.0903, Train Accuracy: 0.8203, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7253/10000, Train Loss: 1.0898, Train Accuracy: 0.8270, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7254/10000, Train Loss: 1.0715, Train Accuracy: 0.8415, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7255/10000, Train Loss: 1.0616, Train Accuracy: 0.8516, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7256/10000, Train Loss: 1.0834, Train Accuracy: 0.8281, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7257/10000, Train Loss: 1.0935, Train Accuracy: 0.8192, Val Loss: 1.1829, Val Accuracy: 0.7232
Epoch 7258/10000, Train Loss: 1.0909, Train Accuracy: 0.8225, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7259/10000, Train Loss: 1.0949, Train Accuracy: 0.8147, Val Loss: 1.1826, Val Accuracy: 0.7321
Epoch 7260/10000, Train Loss: 1.0769, Train Accuracy: 0.8393, Val Loss: 1.1824, Val Accuracy: 0.7321
Epoch 7261/10000, Train Loss: 1.0744, Train Accuracy: 0.8471, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7262/10000, Train Loss: 1.0829, Train Accuracy: 0.8359, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7263/10000, Train Loss: 1.0785, Train Accuracy: 0.8371, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7264/10000, Train Loss: 1.0801, Train Accuracy: 0.8348, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7265/10000, Train Loss: 1.0872, Train Accuracy: 0.8192, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7266/10000, Train Loss: 1.0770, Train Accuracy: 0.8371, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7267/10000, Train Loss: 1.0803, Train Accuracy: 0.8393, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7268/10000, Train Loss: 1.0900, Train Accuracy: 0.8181, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7269/10000, Train Loss: 1.0762, Train Accuracy: 0.8404, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7270/10000, Train Loss: 1.0788, Train Accuracy: 0.8382, Val Loss: 1.1832, Val Accuracy: 0.7321
Epoch 7271/10000, Train Loss: 1.0823, Train Accuracy: 0.8348, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7272/10000, Train Loss: 1.0786, Train Accuracy: 0.8393, Val Loss: 1.1832, Val Accuracy: 0.7321
Epoch 7273/10000, Train Loss: 1.0892, Train Accuracy: 0.8281, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7274/10000, Train Loss: 1.0743, Train Accuracy: 0.8371, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7275/10000, Train Loss: 1.0829, Train Accuracy: 0.8315, Val Loss: 1.1832, Val Accuracy: 0.7232
Epoch 7276/10000, Train Loss: 1.0783, Train Accuracy: 0.8382, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7277/10000, Train Loss: 1.0820, Train Accuracy: 0.8315, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7278/10000, Train Loss: 1.0666, Train Accuracy: 0.8493, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7279/10000, Train Loss: 1.0864, Train Accuracy: 0.8248, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7280/10000, Train Loss: 1.0834, Train Accuracy: 0.8281, Val Loss: 1.1838, Val Accuracy: 0.7232
Epoch 7281/10000, Train Loss: 1.0743, Train Accuracy: 0.8449, Val Loss: 1.1839, Val Accuracy: 0.7188
Epoch 7282/10000, Train Loss: 1.0836, Train Accuracy: 0.8270, Val Loss: 1.1841, Val Accuracy: 0.7232
Epoch 7283/10000, Train Loss: 1.0919, Train Accuracy: 0.8170, Val Loss: 1.1840, Val Accuracy: 0.7232
Epoch 7284/10000, Train Loss: 1.0790, Train Accuracy: 0.8359, Val Loss: 1.1841, Val Accuracy: 0.7232
Epoch 7285/10000, Train Loss: 1.0776, Train Accuracy: 0.8404, Val Loss: 1.1840, Val Accuracy: 0.7188
Epoch 7286/10000, Train Loss: 1.0841, Train Accuracy: 0.8359, Val Loss: 1.1838, Val Accuracy: 0.7232
Epoch 7287/10000, Train Loss: 1.0805, Train Accuracy: 0.8259, Val Loss: 1.1838, Val Accuracy: 0.7188
Epoch 7288/10000, Train Loss: 1.0689, Train Accuracy: 0.8438, Val Loss: 1.1835, Val Accuracy: 0.7232
Epoch 7289/10000, Train Loss: 1.0731, Train Accuracy: 0.8371, Val Loss: 1.1835, Val Accuracy: 0.7232
Epoch 7290/10000, Train Loss: 1.0733, Train Accuracy: 0.8382, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7291/10000, Train Loss: 1.0769, Train Accuracy: 0.8415, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7292/10000, Train Loss: 1.0804, Train Accuracy: 0.8292, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7293/10000, Train Loss: 1.0683, Train Accuracy: 0.8504, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7294/10000, Train Loss: 1.0800, Train Accuracy: 0.8292, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7295/10000, Train Loss: 1.0815, Train Accuracy: 0.8315, Val Loss: 1.1834, Val Accuracy: 0.7232
Epoch 7296/10000, Train Loss: 1.0761, Train Accuracy: 0.8382, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7297/10000, Train Loss: 1.0821, Train Accuracy: 0.8259, Val Loss: 1.1833, Val Accuracy: 0.7188
Epoch 7298/10000, Train Loss: 1.0808, Train Accuracy: 0.8237, Val Loss: 1.1834, Val Accuracy: 0.7188
Epoch 7299/10000, Train Loss: 1.0848, Train Accuracy: 0.8259, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7300/10000, Train Loss: 1.0807, Train Accuracy: 0.8315, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7301/10000, Train Loss: 1.0884, Train Accuracy: 0.8203, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7302/10000, Train Loss: 1.0807, Train Accuracy: 0.8315, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7303/10000, Train Loss: 1.0767, Train Accuracy: 0.8348, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7304/10000, Train Loss: 1.0854, Train Accuracy: 0.8270, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7305/10000, Train Loss: 1.0735, Train Accuracy: 0.8471, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7306/10000, Train Loss: 1.0749, Train Accuracy: 0.8415, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7307/10000, Train Loss: 1.0796, Train Accuracy: 0.8371, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7308/10000, Train Loss: 1.0725, Train Accuracy: 0.8426, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7309/10000, Train Loss: 1.0836, Train Accuracy: 0.8359, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7310/10000, Train Loss: 1.0774, Train Accuracy: 0.8337, Val Loss: 1.1841, Val Accuracy: 0.7277
Epoch 7311/10000, Train Loss: 1.0778, Train Accuracy: 0.8348, Val Loss: 1.1844, Val Accuracy: 0.7277
Epoch 7312/10000, Train Loss: 1.0857, Train Accuracy: 0.8248, Val Loss: 1.1845, Val Accuracy: 0.7277
Epoch 7313/10000, Train Loss: 1.0818, Train Accuracy: 0.8337, Val Loss: 1.1848, Val Accuracy: 0.7277
Epoch 7314/10000, Train Loss: 1.0745, Train Accuracy: 0.8371, Val Loss: 1.1845, Val Accuracy: 0.7277
Epoch 7315/10000, Train Loss: 1.0783, Train Accuracy: 0.8348, Val Loss: 1.1847, Val Accuracy: 0.7232
Epoch 7316/10000, Train Loss: 1.0805, Train Accuracy: 0.8315, Val Loss: 1.1842, Val Accuracy: 0.7277
Epoch 7317/10000, Train Loss: 1.0988, Train Accuracy: 0.8058, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7318/10000, Train Loss: 1.0772, Train Accuracy: 0.8348, Val Loss: 1.1840, Val Accuracy: 0.7277
Epoch 7319/10000, Train Loss: 1.0768, Train Accuracy: 0.8393, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7320/10000, Train Loss: 1.0862, Train Accuracy: 0.8147, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7321/10000, Train Loss: 1.0738, Train Accuracy: 0.8415, Val Loss: 1.1837, Val Accuracy: 0.7277
Epoch 7322/10000, Train Loss: 1.0811, Train Accuracy: 0.8337, Val Loss: 1.1840, Val Accuracy: 0.7277
Epoch 7323/10000, Train Loss: 1.0717, Train Accuracy: 0.8315, Val Loss: 1.1842, Val Accuracy: 0.7277
Epoch 7324/10000, Train Loss: 1.0697, Train Accuracy: 0.8382, Val Loss: 1.1840, Val Accuracy: 0.7277
Epoch 7325/10000, Train Loss: 1.0782, Train Accuracy: 0.8359, Val Loss: 1.1837, Val Accuracy: 0.7277
Epoch 7326/10000, Train Loss: 1.0835, Train Accuracy: 0.8237, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7327/10000, Train Loss: 1.0805, Train Accuracy: 0.8292, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7328/10000, Train Loss: 1.0795, Train Accuracy: 0.8304, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7329/10000, Train Loss: 1.0646, Train Accuracy: 0.8538, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7330/10000, Train Loss: 1.0700, Train Accuracy: 0.8460, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7331/10000, Train Loss: 1.0741, Train Accuracy: 0.8382, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7332/10000, Train Loss: 1.0849, Train Accuracy: 0.8225, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7333/10000, Train Loss: 1.0767, Train Accuracy: 0.8382, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7334/10000, Train Loss: 1.0747, Train Accuracy: 0.8359, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7335/10000, Train Loss: 1.0700, Train Accuracy: 0.8426, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7336/10000, Train Loss: 1.0888, Train Accuracy: 0.8237, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7337/10000, Train Loss: 1.0784, Train Accuracy: 0.8348, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7338/10000, Train Loss: 1.0865, Train Accuracy: 0.8259, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7339/10000, Train Loss: 1.0806, Train Accuracy: 0.8304, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7340/10000, Train Loss: 1.0657, Train Accuracy: 0.8493, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7341/10000, Train Loss: 1.0793, Train Accuracy: 0.8382, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7342/10000, Train Loss: 1.0724, Train Accuracy: 0.8404, Val Loss: 1.1840, Val Accuracy: 0.7277
Epoch 7343/10000, Train Loss: 1.0818, Train Accuracy: 0.8371, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7344/10000, Train Loss: 1.0761, Train Accuracy: 0.8371, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7345/10000, Train Loss: 1.0810, Train Accuracy: 0.8337, Val Loss: 1.1843, Val Accuracy: 0.7232
Epoch 7346/10000, Train Loss: 1.0732, Train Accuracy: 0.8460, Val Loss: 1.1839, Val Accuracy: 0.7232
Epoch 7347/10000, Train Loss: 1.0708, Train Accuracy: 0.8348, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7348/10000, Train Loss: 1.0721, Train Accuracy: 0.8471, Val Loss: 1.1837, Val Accuracy: 0.7232
Epoch 7349/10000, Train Loss: 1.0730, Train Accuracy: 0.8404, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7350/10000, Train Loss: 1.0803, Train Accuracy: 0.8315, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7351/10000, Train Loss: 1.0789, Train Accuracy: 0.8348, Val Loss: 1.1832, Val Accuracy: 0.7232
Epoch 7352/10000, Train Loss: 1.0782, Train Accuracy: 0.8371, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7353/10000, Train Loss: 1.0751, Train Accuracy: 0.8348, Val Loss: 1.1832, Val Accuracy: 0.7232
Epoch 7354/10000, Train Loss: 1.0743, Train Accuracy: 0.8359, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7355/10000, Train Loss: 1.0735, Train Accuracy: 0.8449, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7356/10000, Train Loss: 1.0734, Train Accuracy: 0.8415, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7357/10000, Train Loss: 1.0884, Train Accuracy: 0.8248, Val Loss: 1.1832, Val Accuracy: 0.7366
Epoch 7358/10000, Train Loss: 1.0684, Train Accuracy: 0.8583, Val Loss: 1.1831, Val Accuracy: 0.7366
Epoch 7359/10000, Train Loss: 1.0775, Train Accuracy: 0.8326, Val Loss: 1.1833, Val Accuracy: 0.7321
Epoch 7360/10000, Train Loss: 1.0761, Train Accuracy: 0.8438, Val Loss: 1.1833, Val Accuracy: 0.7321
Epoch 7361/10000, Train Loss: 1.0767, Train Accuracy: 0.8315, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7362/10000, Train Loss: 1.0761, Train Accuracy: 0.8371, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7363/10000, Train Loss: 1.0725, Train Accuracy: 0.8393, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7364/10000, Train Loss: 1.0780, Train Accuracy: 0.8315, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7365/10000, Train Loss: 1.0828, Train Accuracy: 0.8270, Val Loss: 1.1837, Val Accuracy: 0.7277
Epoch 7366/10000, Train Loss: 1.0776, Train Accuracy: 0.8337, Val Loss: 1.1839, Val Accuracy: 0.7277
Epoch 7367/10000, Train Loss: 1.0787, Train Accuracy: 0.8348, Val Loss: 1.1838, Val Accuracy: 0.7277
Epoch 7368/10000, Train Loss: 1.0630, Train Accuracy: 0.8471, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7369/10000, Train Loss: 1.0670, Train Accuracy: 0.8493, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7370/10000, Train Loss: 1.0756, Train Accuracy: 0.8393, Val Loss: 1.1834, Val Accuracy: 0.7232
Epoch 7371/10000, Train Loss: 1.0759, Train Accuracy: 0.8404, Val Loss: 1.1834, Val Accuracy: 0.7232
Epoch 7372/10000, Train Loss: 1.0828, Train Accuracy: 0.8248, Val Loss: 1.1835, Val Accuracy: 0.7277
Epoch 7373/10000, Train Loss: 1.0727, Train Accuracy: 0.8471, Val Loss: 1.1836, Val Accuracy: 0.7188
Epoch 7374/10000, Train Loss: 1.0663, Train Accuracy: 0.8415, Val Loss: 1.1837, Val Accuracy: 0.7188
Epoch 7375/10000, Train Loss: 1.0799, Train Accuracy: 0.8326, Val Loss: 1.1836, Val Accuracy: 0.7188
Epoch 7376/10000, Train Loss: 1.0816, Train Accuracy: 0.8259, Val Loss: 1.1839, Val Accuracy: 0.7188
Epoch 7377/10000, Train Loss: 1.0765, Train Accuracy: 0.8348, Val Loss: 1.1837, Val Accuracy: 0.7188
Epoch 7378/10000, Train Loss: 1.0764, Train Accuracy: 0.8382, Val Loss: 1.1836, Val Accuracy: 0.7188
Epoch 7379/10000, Train Loss: 1.0877, Train Accuracy: 0.8192, Val Loss: 1.1835, Val Accuracy: 0.7188
Epoch 7380/10000, Train Loss: 1.0866, Train Accuracy: 0.8248, Val Loss: 1.1833, Val Accuracy: 0.7188
Epoch 7381/10000, Train Loss: 1.0874, Train Accuracy: 0.8281, Val Loss: 1.1835, Val Accuracy: 0.7188
Epoch 7382/10000, Train Loss: 1.0719, Train Accuracy: 0.8393, Val Loss: 1.1835, Val Accuracy: 0.7188
Epoch 7383/10000, Train Loss: 1.0795, Train Accuracy: 0.8304, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7384/10000, Train Loss: 1.0847, Train Accuracy: 0.8248, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7385/10000, Train Loss: 1.0839, Train Accuracy: 0.8248, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7386/10000, Train Loss: 1.0741, Train Accuracy: 0.8315, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7387/10000, Train Loss: 1.0893, Train Accuracy: 0.8203, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7388/10000, Train Loss: 1.0654, Train Accuracy: 0.8516, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7389/10000, Train Loss: 1.0737, Train Accuracy: 0.8449, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7390/10000, Train Loss: 1.0791, Train Accuracy: 0.8315, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7391/10000, Train Loss: 1.0774, Train Accuracy: 0.8371, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7392/10000, Train Loss: 1.0659, Train Accuracy: 0.8404, Val Loss: 1.1832, Val Accuracy: 0.7321
Epoch 7393/10000, Train Loss: 1.0654, Train Accuracy: 0.8471, Val Loss: 1.1831, Val Accuracy: 0.7321
Epoch 7394/10000, Train Loss: 1.0710, Train Accuracy: 0.8426, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7395/10000, Train Loss: 1.0748, Train Accuracy: 0.8359, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7396/10000, Train Loss: 1.0697, Train Accuracy: 0.8426, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7397/10000, Train Loss: 1.0764, Train Accuracy: 0.8359, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7398/10000, Train Loss: 1.0770, Train Accuracy: 0.8382, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7399/10000, Train Loss: 1.0641, Train Accuracy: 0.8538, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7400/10000, Train Loss: 1.0816, Train Accuracy: 0.8270, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7401/10000, Train Loss: 1.0876, Train Accuracy: 0.8214, Val Loss: 1.1832, Val Accuracy: 0.7232
Epoch 7402/10000, Train Loss: 1.0798, Train Accuracy: 0.8326, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7403/10000, Train Loss: 1.0804, Train Accuracy: 0.8326, Val Loss: 1.1830, Val Accuracy: 0.7188
Epoch 7404/10000, Train Loss: 1.0724, Train Accuracy: 0.8404, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7405/10000, Train Loss: 1.0707, Train Accuracy: 0.8482, Val Loss: 1.1833, Val Accuracy: 0.7188
Epoch 7406/10000, Train Loss: 1.0730, Train Accuracy: 0.8337, Val Loss: 1.1831, Val Accuracy: 0.7188
Epoch 7407/10000, Train Loss: 1.0780, Train Accuracy: 0.8304, Val Loss: 1.1828, Val Accuracy: 0.7188
Epoch 7408/10000, Train Loss: 1.0798, Train Accuracy: 0.8348, Val Loss: 1.1828, Val Accuracy: 0.7188
Epoch 7409/10000, Train Loss: 1.0807, Train Accuracy: 0.8326, Val Loss: 1.1827, Val Accuracy: 0.7232
Epoch 7410/10000, Train Loss: 1.0828, Train Accuracy: 0.8281, Val Loss: 1.1827, Val Accuracy: 0.7188
Epoch 7411/10000, Train Loss: 1.0799, Train Accuracy: 0.8348, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7412/10000, Train Loss: 1.0779, Train Accuracy: 0.8281, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7413/10000, Train Loss: 1.0764, Train Accuracy: 0.8348, Val Loss: 1.1829, Val Accuracy: 0.7232
Epoch 7414/10000, Train Loss: 1.0751, Train Accuracy: 0.8337, Val Loss: 1.1827, Val Accuracy: 0.7232
Epoch 7415/10000, Train Loss: 1.0560, Train Accuracy: 0.8583, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7416/10000, Train Loss: 1.0771, Train Accuracy: 0.8371, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7417/10000, Train Loss: 1.0738, Train Accuracy: 0.8337, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7418/10000, Train Loss: 1.0752, Train Accuracy: 0.8382, Val Loss: 1.1829, Val Accuracy: 0.7321
Epoch 7419/10000, Train Loss: 1.0798, Train Accuracy: 0.8315, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7420/10000, Train Loss: 1.0589, Train Accuracy: 0.8571, Val Loss: 1.1826, Val Accuracy: 0.7321
Epoch 7421/10000, Train Loss: 1.0827, Train Accuracy: 0.8315, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7422/10000, Train Loss: 1.0716, Train Accuracy: 0.8393, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7423/10000, Train Loss: 1.0613, Train Accuracy: 0.8538, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7424/10000, Train Loss: 1.0748, Train Accuracy: 0.8404, Val Loss: 1.1830, Val Accuracy: 0.7321
Epoch 7425/10000, Train Loss: 1.0747, Train Accuracy: 0.8393, Val Loss: 1.1826, Val Accuracy: 0.7321
Epoch 7426/10000, Train Loss: 1.0717, Train Accuracy: 0.8482, Val Loss: 1.1827, Val Accuracy: 0.7321
Epoch 7427/10000, Train Loss: 1.0623, Train Accuracy: 0.8583, Val Loss: 1.1825, Val Accuracy: 0.7321
Epoch 7428/10000, Train Loss: 1.0720, Train Accuracy: 0.8460, Val Loss: 1.1829, Val Accuracy: 0.7366
Epoch 7429/10000, Train Loss: 1.0823, Train Accuracy: 0.8348, Val Loss: 1.1831, Val Accuracy: 0.7277
Epoch 7430/10000, Train Loss: 1.0737, Train Accuracy: 0.8438, Val Loss: 1.1827, Val Accuracy: 0.7232
Epoch 7431/10000, Train Loss: 1.0875, Train Accuracy: 0.8281, Val Loss: 1.1830, Val Accuracy: 0.7232
Epoch 7432/10000, Train Loss: 1.0736, Train Accuracy: 0.8371, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7433/10000, Train Loss: 1.0812, Train Accuracy: 0.8281, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7434/10000, Train Loss: 1.0791, Train Accuracy: 0.8393, Val Loss: 1.1834, Val Accuracy: 0.7188
Epoch 7435/10000, Train Loss: 1.0821, Train Accuracy: 0.8281, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7436/10000, Train Loss: 1.0724, Train Accuracy: 0.8326, Val Loss: 1.1834, Val Accuracy: 0.7232
Epoch 7437/10000, Train Loss: 1.0679, Train Accuracy: 0.8482, Val Loss: 1.1836, Val Accuracy: 0.7277
Epoch 7438/10000, Train Loss: 1.0662, Train Accuracy: 0.8449, Val Loss: 1.1836, Val Accuracy: 0.7232
Epoch 7439/10000, Train Loss: 1.0771, Train Accuracy: 0.8359, Val Loss: 1.1834, Val Accuracy: 0.7321
Epoch 7440/10000, Train Loss: 1.0780, Train Accuracy: 0.8393, Val Loss: 1.1832, Val Accuracy: 0.7277
Epoch 7441/10000, Train Loss: 1.0701, Train Accuracy: 0.8471, Val Loss: 1.1833, Val Accuracy: 0.7277
Epoch 7442/10000, Train Loss: 1.0772, Train Accuracy: 0.8304, Val Loss: 1.1834, Val Accuracy: 0.7277
Epoch 7443/10000, Train Loss: 1.0809, Train Accuracy: 0.8348, Val Loss: 1.1835, Val Accuracy: 0.7232
Epoch 7444/10000, Train Loss: 1.0848, Train Accuracy: 0.8281, Val Loss: 1.1833, Val Accuracy: 0.7232
Epoch 7445/10000, Train Loss: 1.0728, Train Accuracy: 0.8404, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7446/10000, Train Loss: 1.0705, Train Accuracy: 0.8404, Val Loss: 1.1834, Val Accuracy: 0.7188
Epoch 7447/10000, Train Loss: 1.0596, Train Accuracy: 0.8571, Val Loss: 1.1835, Val Accuracy: 0.7143
Epoch 7448/10000, Train Loss: 1.0716, Train Accuracy: 0.8404, Val Loss: 1.1833, Val Accuracy: 0.7188
Epoch 7449/10000, Train Loss: 1.0894, Train Accuracy: 0.8158, Val Loss: 1.1833, Val Accuracy: 0.7188
Epoch 7450/10000, Train Loss: 1.0774, Train Accuracy: 0.8359, Val Loss: 1.1830, Val Accuracy: 0.7188
Epoch 7451/10000, Train Loss: 1.0750, Train Accuracy: 0.8393, Val Loss: 1.1831, Val Accuracy: 0.7232
Epoch 7452/10000, Train Loss: 1.0605, Train Accuracy: 0.8527, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7453/10000, Train Loss: 1.0809, Train Accuracy: 0.8270, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7454/10000, Train Loss: 1.0729, Train Accuracy: 0.8404, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7455/10000, Train Loss: 1.0716, Train Accuracy: 0.8460, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7456/10000, Train Loss: 1.0737, Train Accuracy: 0.8393, Val Loss: 1.1827, Val Accuracy: 0.7232
Epoch 7457/10000, Train Loss: 1.0769, Train Accuracy: 0.8337, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7458/10000, Train Loss: 1.0799, Train Accuracy: 0.8304, Val Loss: 1.1824, Val Accuracy: 0.7232
Epoch 7459/10000, Train Loss: 1.0744, Train Accuracy: 0.8449, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7460/10000, Train Loss: 1.0742, Train Accuracy: 0.8382, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7461/10000, Train Loss: 1.0675, Train Accuracy: 0.8449, Val Loss: 1.1824, Val Accuracy: 0.7232
Epoch 7462/10000, Train Loss: 1.0758, Train Accuracy: 0.8359, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7463/10000, Train Loss: 1.0763, Train Accuracy: 0.8315, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7464/10000, Train Loss: 1.0719, Train Accuracy: 0.8359, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7465/10000, Train Loss: 1.0585, Train Accuracy: 0.8516, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7466/10000, Train Loss: 1.0652, Train Accuracy: 0.8438, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7467/10000, Train Loss: 1.0626, Train Accuracy: 0.8538, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7468/10000, Train Loss: 1.0750, Train Accuracy: 0.8393, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7469/10000, Train Loss: 1.0691, Train Accuracy: 0.8482, Val Loss: 1.1819, Val Accuracy: 0.7321
Epoch 7470/10000, Train Loss: 1.0748, Train Accuracy: 0.8404, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7471/10000, Train Loss: 1.0853, Train Accuracy: 0.8281, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7472/10000, Train Loss: 1.0780, Train Accuracy: 0.8404, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7473/10000, Train Loss: 1.0710, Train Accuracy: 0.8382, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7474/10000, Train Loss: 1.0825, Train Accuracy: 0.8315, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7475/10000, Train Loss: 1.0735, Train Accuracy: 0.8415, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7476/10000, Train Loss: 1.0832, Train Accuracy: 0.8326, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7477/10000, Train Loss: 1.0663, Train Accuracy: 0.8426, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7478/10000, Train Loss: 1.0760, Train Accuracy: 0.8326, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7479/10000, Train Loss: 1.0776, Train Accuracy: 0.8315, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7480/10000, Train Loss: 1.0705, Train Accuracy: 0.8438, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7481/10000, Train Loss: 1.0707, Train Accuracy: 0.8404, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7482/10000, Train Loss: 1.0697, Train Accuracy: 0.8471, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7483/10000, Train Loss: 1.0724, Train Accuracy: 0.8404, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7484/10000, Train Loss: 1.0808, Train Accuracy: 0.8382, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7485/10000, Train Loss: 1.0822, Train Accuracy: 0.8270, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7486/10000, Train Loss: 1.0734, Train Accuracy: 0.8404, Val Loss: 1.1822, Val Accuracy: 0.7321
Epoch 7487/10000, Train Loss: 1.0762, Train Accuracy: 0.8348, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7488/10000, Train Loss: 1.0668, Train Accuracy: 0.8504, Val Loss: 1.1818, Val Accuracy: 0.7321
Epoch 7489/10000, Train Loss: 1.0746, Train Accuracy: 0.8292, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7490/10000, Train Loss: 1.0778, Train Accuracy: 0.8404, Val Loss: 1.1820, Val Accuracy: 0.7321
Epoch 7491/10000, Train Loss: 1.0849, Train Accuracy: 0.8248, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7492/10000, Train Loss: 1.0644, Train Accuracy: 0.8482, Val Loss: 1.1821, Val Accuracy: 0.7321
Epoch 7493/10000, Train Loss: 1.0711, Train Accuracy: 0.8382, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7494/10000, Train Loss: 1.0816, Train Accuracy: 0.8281, Val Loss: 1.1815, Val Accuracy: 0.7277
Epoch 7495/10000, Train Loss: 1.0790, Train Accuracy: 0.8259, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7496/10000, Train Loss: 1.0718, Train Accuracy: 0.8449, Val Loss: 1.1815, Val Accuracy: 0.7277
Epoch 7497/10000, Train Loss: 1.0769, Train Accuracy: 0.8426, Val Loss: 1.1815, Val Accuracy: 0.7277
Epoch 7498/10000, Train Loss: 1.0843, Train Accuracy: 0.8248, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7499/10000, Train Loss: 1.0616, Train Accuracy: 0.8538, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7500/10000, Train Loss: 1.0724, Train Accuracy: 0.8371, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7501/10000, Train Loss: 1.0819, Train Accuracy: 0.8326, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7502/10000, Train Loss: 1.0583, Train Accuracy: 0.8516, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7503/10000, Train Loss: 1.0851, Train Accuracy: 0.8214, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7504/10000, Train Loss: 1.0635, Train Accuracy: 0.8438, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7505/10000, Train Loss: 1.0748, Train Accuracy: 0.8382, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7506/10000, Train Loss: 1.0720, Train Accuracy: 0.8482, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7507/10000, Train Loss: 1.0789, Train Accuracy: 0.8326, Val Loss: 1.1818, Val Accuracy: 0.7321
Epoch 7508/10000, Train Loss: 1.0829, Train Accuracy: 0.8281, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7509/10000, Train Loss: 1.0765, Train Accuracy: 0.8371, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7510/10000, Train Loss: 1.0752, Train Accuracy: 0.8426, Val Loss: 1.1814, Val Accuracy: 0.7321
Epoch 7511/10000, Train Loss: 1.0789, Train Accuracy: 0.8315, Val Loss: 1.1813, Val Accuracy: 0.7321
Epoch 7512/10000, Train Loss: 1.0765, Train Accuracy: 0.8315, Val Loss: 1.1812, Val Accuracy: 0.7321
Epoch 7513/10000, Train Loss: 1.0821, Train Accuracy: 0.8237, Val Loss: 1.1816, Val Accuracy: 0.7321
Epoch 7514/10000, Train Loss: 1.0865, Train Accuracy: 0.8225, Val Loss: 1.1817, Val Accuracy: 0.7321
Epoch 7515/10000, Train Loss: 1.0730, Train Accuracy: 0.8382, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7516/10000, Train Loss: 1.0777, Train Accuracy: 0.8337, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7517/10000, Train Loss: 1.0750, Train Accuracy: 0.8371, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7518/10000, Train Loss: 1.0571, Train Accuracy: 0.8583, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7519/10000, Train Loss: 1.0598, Train Accuracy: 0.8560, Val Loss: 1.1825, Val Accuracy: 0.7232
Epoch 7520/10000, Train Loss: 1.0819, Train Accuracy: 0.8203, Val Loss: 1.1828, Val Accuracy: 0.7232
Epoch 7521/10000, Train Loss: 1.0885, Train Accuracy: 0.8270, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7522/10000, Train Loss: 1.0770, Train Accuracy: 0.8393, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7523/10000, Train Loss: 1.0894, Train Accuracy: 0.8192, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7524/10000, Train Loss: 1.0769, Train Accuracy: 0.8371, Val Loss: 1.1826, Val Accuracy: 0.7232
Epoch 7525/10000, Train Loss: 1.0723, Train Accuracy: 0.8371, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7526/10000, Train Loss: 1.0830, Train Accuracy: 0.8225, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7527/10000, Train Loss: 1.0881, Train Accuracy: 0.8203, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7528/10000, Train Loss: 1.0636, Train Accuracy: 0.8516, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7529/10000, Train Loss: 1.0716, Train Accuracy: 0.8438, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7530/10000, Train Loss: 1.0720, Train Accuracy: 0.8393, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7531/10000, Train Loss: 1.0674, Train Accuracy: 0.8471, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7532/10000, Train Loss: 1.0593, Train Accuracy: 0.8527, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7533/10000, Train Loss: 1.0717, Train Accuracy: 0.8382, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7534/10000, Train Loss: 1.0707, Train Accuracy: 0.8326, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7535/10000, Train Loss: 1.0848, Train Accuracy: 0.8225, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7536/10000, Train Loss: 1.0738, Train Accuracy: 0.8438, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7537/10000, Train Loss: 1.0618, Train Accuracy: 0.8493, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7538/10000, Train Loss: 1.0768, Train Accuracy: 0.8348, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7539/10000, Train Loss: 1.0768, Train Accuracy: 0.8348, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7540/10000, Train Loss: 1.0734, Train Accuracy: 0.8382, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7541/10000, Train Loss: 1.0761, Train Accuracy: 0.8326, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7542/10000, Train Loss: 1.0704, Train Accuracy: 0.8438, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7543/10000, Train Loss: 1.0803, Train Accuracy: 0.8304, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7544/10000, Train Loss: 1.0689, Train Accuracy: 0.8426, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7545/10000, Train Loss: 1.0737, Train Accuracy: 0.8449, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7546/10000, Train Loss: 1.0685, Train Accuracy: 0.8460, Val Loss: 1.1830, Val Accuracy: 0.7277
Epoch 7547/10000, Train Loss: 1.0763, Train Accuracy: 0.8371, Val Loss: 1.1829, Val Accuracy: 0.7277
Epoch 7548/10000, Train Loss: 1.0771, Train Accuracy: 0.8393, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7549/10000, Train Loss: 1.0721, Train Accuracy: 0.8426, Val Loss: 1.1828, Val Accuracy: 0.7277
Epoch 7550/10000, Train Loss: 1.0762, Train Accuracy: 0.8315, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7551/10000, Train Loss: 1.0716, Train Accuracy: 0.8438, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7552/10000, Train Loss: 1.0720, Train Accuracy: 0.8393, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7553/10000, Train Loss: 1.0703, Train Accuracy: 0.8449, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7554/10000, Train Loss: 1.0685, Train Accuracy: 0.8471, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7555/10000, Train Loss: 1.0758, Train Accuracy: 0.8359, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7556/10000, Train Loss: 1.0671, Train Accuracy: 0.8504, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7557/10000, Train Loss: 1.0760, Train Accuracy: 0.8393, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7558/10000, Train Loss: 1.0793, Train Accuracy: 0.8348, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7559/10000, Train Loss: 1.0706, Train Accuracy: 0.8393, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7560/10000, Train Loss: 1.0710, Train Accuracy: 0.8382, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7561/10000, Train Loss: 1.0693, Train Accuracy: 0.8404, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7562/10000, Train Loss: 1.0767, Train Accuracy: 0.8326, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7563/10000, Train Loss: 1.0873, Train Accuracy: 0.8192, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7564/10000, Train Loss: 1.0768, Train Accuracy: 0.8348, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7565/10000, Train Loss: 1.0751, Train Accuracy: 0.8482, Val Loss: 1.1827, Val Accuracy: 0.7277
Epoch 7566/10000, Train Loss: 1.0762, Train Accuracy: 0.8337, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7567/10000, Train Loss: 1.0646, Train Accuracy: 0.8493, Val Loss: 1.1826, Val Accuracy: 0.7277
Epoch 7568/10000, Train Loss: 1.0716, Train Accuracy: 0.8426, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7569/10000, Train Loss: 1.0666, Train Accuracy: 0.8438, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7570/10000, Train Loss: 1.0739, Train Accuracy: 0.8438, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7571/10000, Train Loss: 1.0895, Train Accuracy: 0.8125, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7572/10000, Train Loss: 1.0700, Train Accuracy: 0.8426, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7573/10000, Train Loss: 1.0766, Train Accuracy: 0.8348, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7574/10000, Train Loss: 1.0729, Train Accuracy: 0.8382, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7575/10000, Train Loss: 1.0746, Train Accuracy: 0.8348, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7576/10000, Train Loss: 1.0876, Train Accuracy: 0.8270, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7577/10000, Train Loss: 1.0790, Train Accuracy: 0.8292, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7578/10000, Train Loss: 1.0650, Train Accuracy: 0.8493, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7579/10000, Train Loss: 1.0640, Train Accuracy: 0.8527, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7580/10000, Train Loss: 1.0863, Train Accuracy: 0.8203, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7581/10000, Train Loss: 1.0670, Train Accuracy: 0.8460, Val Loss: 1.1824, Val Accuracy: 0.7277
Epoch 7582/10000, Train Loss: 1.0851, Train Accuracy: 0.8292, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7583/10000, Train Loss: 1.0688, Train Accuracy: 0.8404, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7584/10000, Train Loss: 1.0628, Train Accuracy: 0.8426, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7585/10000, Train Loss: 1.0809, Train Accuracy: 0.8248, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7586/10000, Train Loss: 1.0687, Train Accuracy: 0.8493, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7587/10000, Train Loss: 1.0631, Train Accuracy: 0.8460, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7588/10000, Train Loss: 1.0732, Train Accuracy: 0.8438, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7589/10000, Train Loss: 1.0722, Train Accuracy: 0.8371, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7590/10000, Train Loss: 1.0667, Train Accuracy: 0.8471, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7591/10000, Train Loss: 1.0666, Train Accuracy: 0.8426, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7592/10000, Train Loss: 1.0718, Train Accuracy: 0.8449, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7593/10000, Train Loss: 1.0633, Train Accuracy: 0.8538, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7594/10000, Train Loss: 1.0722, Train Accuracy: 0.8426, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7595/10000, Train Loss: 1.0633, Train Accuracy: 0.8527, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7596/10000, Train Loss: 1.0763, Train Accuracy: 0.8382, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7597/10000, Train Loss: 1.0786, Train Accuracy: 0.8270, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7598/10000, Train Loss: 1.0694, Train Accuracy: 0.8449, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7599/10000, Train Loss: 1.0721, Train Accuracy: 0.8393, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7600/10000, Train Loss: 1.0726, Train Accuracy: 0.8348, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7601/10000, Train Loss: 1.0760, Train Accuracy: 0.8337, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7602/10000, Train Loss: 1.0894, Train Accuracy: 0.8092, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7603/10000, Train Loss: 1.0776, Train Accuracy: 0.8393, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7604/10000, Train Loss: 1.0779, Train Accuracy: 0.8326, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7605/10000, Train Loss: 1.0745, Train Accuracy: 0.8404, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7606/10000, Train Loss: 1.0690, Train Accuracy: 0.8460, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7607/10000, Train Loss: 1.0766, Train Accuracy: 0.8315, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7608/10000, Train Loss: 1.0817, Train Accuracy: 0.8337, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7609/10000, Train Loss: 1.0805, Train Accuracy: 0.8304, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7610/10000, Train Loss: 1.0649, Train Accuracy: 0.8460, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7611/10000, Train Loss: 1.0777, Train Accuracy: 0.8382, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7612/10000, Train Loss: 1.0782, Train Accuracy: 0.8315, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7613/10000, Train Loss: 1.0747, Train Accuracy: 0.8460, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7614/10000, Train Loss: 1.0779, Train Accuracy: 0.8348, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7615/10000, Train Loss: 1.0699, Train Accuracy: 0.8527, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7616/10000, Train Loss: 1.0664, Train Accuracy: 0.8438, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7617/10000, Train Loss: 1.0650, Train Accuracy: 0.8482, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7618/10000, Train Loss: 1.0821, Train Accuracy: 0.8337, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7619/10000, Train Loss: 1.0750, Train Accuracy: 0.8426, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7620/10000, Train Loss: 1.0641, Train Accuracy: 0.8493, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7621/10000, Train Loss: 1.0819, Train Accuracy: 0.8237, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7622/10000, Train Loss: 1.0725, Train Accuracy: 0.8449, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7623/10000, Train Loss: 1.0670, Train Accuracy: 0.8426, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7624/10000, Train Loss: 1.0738, Train Accuracy: 0.8359, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7625/10000, Train Loss: 1.0671, Train Accuracy: 0.8438, Val Loss: 1.1819, Val Accuracy: 0.7232
Epoch 7626/10000, Train Loss: 1.0708, Train Accuracy: 0.8404, Val Loss: 1.1816, Val Accuracy: 0.7232
Epoch 7627/10000, Train Loss: 1.0767, Train Accuracy: 0.8292, Val Loss: 1.1815, Val Accuracy: 0.7232
Epoch 7628/10000, Train Loss: 1.0674, Train Accuracy: 0.8460, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7629/10000, Train Loss: 1.0701, Train Accuracy: 0.8438, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7630/10000, Train Loss: 1.0728, Train Accuracy: 0.8426, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7631/10000, Train Loss: 1.0705, Train Accuracy: 0.8415, Val Loss: 1.1815, Val Accuracy: 0.7232
Epoch 7632/10000, Train Loss: 1.0696, Train Accuracy: 0.8415, Val Loss: 1.1816, Val Accuracy: 0.7232
Epoch 7633/10000, Train Loss: 1.0682, Train Accuracy: 0.8371, Val Loss: 1.1816, Val Accuracy: 0.7232
Epoch 7634/10000, Train Loss: 1.0751, Train Accuracy: 0.8371, Val Loss: 1.1814, Val Accuracy: 0.7232
Epoch 7635/10000, Train Loss: 1.0664, Train Accuracy: 0.8404, Val Loss: 1.1817, Val Accuracy: 0.7232
Epoch 7636/10000, Train Loss: 1.0785, Train Accuracy: 0.8292, Val Loss: 1.1815, Val Accuracy: 0.7232
Epoch 7637/10000, Train Loss: 1.0774, Train Accuracy: 0.8315, Val Loss: 1.1814, Val Accuracy: 0.7232
Epoch 7638/10000, Train Loss: 1.0673, Train Accuracy: 0.8482, Val Loss: 1.1813, Val Accuracy: 0.7232
Epoch 7639/10000, Train Loss: 1.0549, Train Accuracy: 0.8638, Val Loss: 1.1812, Val Accuracy: 0.7232
Epoch 7640/10000, Train Loss: 1.0633, Train Accuracy: 0.8527, Val Loss: 1.1811, Val Accuracy: 0.7232
Epoch 7641/10000, Train Loss: 1.0629, Train Accuracy: 0.8516, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7642/10000, Train Loss: 1.0692, Train Accuracy: 0.8438, Val Loss: 1.1809, Val Accuracy: 0.7232
Epoch 7643/10000, Train Loss: 1.0692, Train Accuracy: 0.8471, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7644/10000, Train Loss: 1.0764, Train Accuracy: 0.8404, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7645/10000, Train Loss: 1.0638, Train Accuracy: 0.8504, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7646/10000, Train Loss: 1.0713, Train Accuracy: 0.8292, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7647/10000, Train Loss: 1.0664, Train Accuracy: 0.8538, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7648/10000, Train Loss: 1.0639, Train Accuracy: 0.8560, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7649/10000, Train Loss: 1.0720, Train Accuracy: 0.8393, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7650/10000, Train Loss: 1.0742, Train Accuracy: 0.8438, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7651/10000, Train Loss: 1.0735, Train Accuracy: 0.8371, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7652/10000, Train Loss: 1.0609, Train Accuracy: 0.8527, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7653/10000, Train Loss: 1.0590, Train Accuracy: 0.8482, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7654/10000, Train Loss: 1.0583, Train Accuracy: 0.8527, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7655/10000, Train Loss: 1.0733, Train Accuracy: 0.8449, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7656/10000, Train Loss: 1.0688, Train Accuracy: 0.8482, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7657/10000, Train Loss: 1.0625, Train Accuracy: 0.8516, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7658/10000, Train Loss: 1.0599, Train Accuracy: 0.8527, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7659/10000, Train Loss: 1.0760, Train Accuracy: 0.8404, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7660/10000, Train Loss: 1.0683, Train Accuracy: 0.8471, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7661/10000, Train Loss: 1.0706, Train Accuracy: 0.8404, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7662/10000, Train Loss: 1.0621, Train Accuracy: 0.8516, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7663/10000, Train Loss: 1.0683, Train Accuracy: 0.8415, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7664/10000, Train Loss: 1.0727, Train Accuracy: 0.8404, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7665/10000, Train Loss: 1.0651, Train Accuracy: 0.8549, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7666/10000, Train Loss: 1.0653, Train Accuracy: 0.8471, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7667/10000, Train Loss: 1.0653, Train Accuracy: 0.8449, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7668/10000, Train Loss: 1.0718, Train Accuracy: 0.8371, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7669/10000, Train Loss: 1.0741, Train Accuracy: 0.8348, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7670/10000, Train Loss: 1.0710, Train Accuracy: 0.8371, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7671/10000, Train Loss: 1.0688, Train Accuracy: 0.8371, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7672/10000, Train Loss: 1.0682, Train Accuracy: 0.8471, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7673/10000, Train Loss: 1.0686, Train Accuracy: 0.8415, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7674/10000, Train Loss: 1.0634, Train Accuracy: 0.8516, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7675/10000, Train Loss: 1.0598, Train Accuracy: 0.8527, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7676/10000, Train Loss: 1.0640, Train Accuracy: 0.8460, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7677/10000, Train Loss: 1.0698, Train Accuracy: 0.8337, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7678/10000, Train Loss: 1.0756, Train Accuracy: 0.8371, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7679/10000, Train Loss: 1.0628, Train Accuracy: 0.8482, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7680/10000, Train Loss: 1.0694, Train Accuracy: 0.8471, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7681/10000, Train Loss: 1.0678, Train Accuracy: 0.8471, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7682/10000, Train Loss: 1.0753, Train Accuracy: 0.8404, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7683/10000, Train Loss: 1.0609, Train Accuracy: 0.8571, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7684/10000, Train Loss: 1.0679, Train Accuracy: 0.8449, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7685/10000, Train Loss: 1.0784, Train Accuracy: 0.8371, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7686/10000, Train Loss: 1.0577, Train Accuracy: 0.8583, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7687/10000, Train Loss: 1.0688, Train Accuracy: 0.8493, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7688/10000, Train Loss: 1.0591, Train Accuracy: 0.8549, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7689/10000, Train Loss: 1.0714, Train Accuracy: 0.8404, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7690/10000, Train Loss: 1.0660, Train Accuracy: 0.8460, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7691/10000, Train Loss: 1.0692, Train Accuracy: 0.8337, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7692/10000, Train Loss: 1.0776, Train Accuracy: 0.8315, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7693/10000, Train Loss: 1.0679, Train Accuracy: 0.8426, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7694/10000, Train Loss: 1.0595, Train Accuracy: 0.8538, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7695/10000, Train Loss: 1.0661, Train Accuracy: 0.8471, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7696/10000, Train Loss: 1.0761, Train Accuracy: 0.8393, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7697/10000, Train Loss: 1.0644, Train Accuracy: 0.8449, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7698/10000, Train Loss: 1.0660, Train Accuracy: 0.8449, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7699/10000, Train Loss: 1.0670, Train Accuracy: 0.8504, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7700/10000, Train Loss: 1.0790, Train Accuracy: 0.8337, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7701/10000, Train Loss: 1.0637, Train Accuracy: 0.8538, Val Loss: 1.1815, Val Accuracy: 0.7277
Epoch 7702/10000, Train Loss: 1.0792, Train Accuracy: 0.8281, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7703/10000, Train Loss: 1.0623, Train Accuracy: 0.8560, Val Loss: 1.1815, Val Accuracy: 0.7277
Epoch 7704/10000, Train Loss: 1.0652, Train Accuracy: 0.8471, Val Loss: 1.1814, Val Accuracy: 0.7232
Epoch 7705/10000, Train Loss: 1.0799, Train Accuracy: 0.8326, Val Loss: 1.1813, Val Accuracy: 0.7232
Epoch 7706/10000, Train Loss: 1.0757, Train Accuracy: 0.8326, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7707/10000, Train Loss: 1.0716, Train Accuracy: 0.8426, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7708/10000, Train Loss: 1.0740, Train Accuracy: 0.8359, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7709/10000, Train Loss: 1.0607, Train Accuracy: 0.8583, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7710/10000, Train Loss: 1.0523, Train Accuracy: 0.8583, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7711/10000, Train Loss: 1.0738, Train Accuracy: 0.8326, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7712/10000, Train Loss: 1.0659, Train Accuracy: 0.8482, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7713/10000, Train Loss: 1.0645, Train Accuracy: 0.8415, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7714/10000, Train Loss: 1.0696, Train Accuracy: 0.8460, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7715/10000, Train Loss: 1.0830, Train Accuracy: 0.8281, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7716/10000, Train Loss: 1.0733, Train Accuracy: 0.8371, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7717/10000, Train Loss: 1.0670, Train Accuracy: 0.8471, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7718/10000, Train Loss: 1.0525, Train Accuracy: 0.8650, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7719/10000, Train Loss: 1.0660, Train Accuracy: 0.8471, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7720/10000, Train Loss: 1.0765, Train Accuracy: 0.8304, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7721/10000, Train Loss: 1.0718, Train Accuracy: 0.8415, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7722/10000, Train Loss: 1.0655, Train Accuracy: 0.8449, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7723/10000, Train Loss: 1.0775, Train Accuracy: 0.8337, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7724/10000, Train Loss: 1.0619, Train Accuracy: 0.8482, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7725/10000, Train Loss: 1.0734, Train Accuracy: 0.8337, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7726/10000, Train Loss: 1.0771, Train Accuracy: 0.8371, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7727/10000, Train Loss: 1.0578, Train Accuracy: 0.8583, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7728/10000, Train Loss: 1.0711, Train Accuracy: 0.8382, Val Loss: 1.1826, Val Accuracy: 0.7232
Epoch 7729/10000, Train Loss: 1.0783, Train Accuracy: 0.8326, Val Loss: 1.1825, Val Accuracy: 0.7277
Epoch 7730/10000, Train Loss: 1.0670, Train Accuracy: 0.8504, Val Loss: 1.1823, Val Accuracy: 0.7277
Epoch 7731/10000, Train Loss: 1.0698, Train Accuracy: 0.8426, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7732/10000, Train Loss: 1.0638, Train Accuracy: 0.8438, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7733/10000, Train Loss: 1.0769, Train Accuracy: 0.8348, Val Loss: 1.1822, Val Accuracy: 0.7277
Epoch 7734/10000, Train Loss: 1.0681, Train Accuracy: 0.8393, Val Loss: 1.1822, Val Accuracy: 0.7232
Epoch 7735/10000, Train Loss: 1.0831, Train Accuracy: 0.8259, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7736/10000, Train Loss: 1.0743, Train Accuracy: 0.8348, Val Loss: 1.1820, Val Accuracy: 0.7277
Epoch 7737/10000, Train Loss: 1.0770, Train Accuracy: 0.8326, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7738/10000, Train Loss: 1.0721, Train Accuracy: 0.8382, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7739/10000, Train Loss: 1.0770, Train Accuracy: 0.8371, Val Loss: 1.1821, Val Accuracy: 0.7232
Epoch 7740/10000, Train Loss: 1.0693, Train Accuracy: 0.8415, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7741/10000, Train Loss: 1.0628, Train Accuracy: 0.8471, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7742/10000, Train Loss: 1.0583, Train Accuracy: 0.8571, Val Loss: 1.1817, Val Accuracy: 0.7277
Epoch 7743/10000, Train Loss: 1.0614, Train Accuracy: 0.8549, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7744/10000, Train Loss: 1.0690, Train Accuracy: 0.8393, Val Loss: 1.1821, Val Accuracy: 0.7277
Epoch 7745/10000, Train Loss: 1.0654, Train Accuracy: 0.8460, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7746/10000, Train Loss: 1.0598, Train Accuracy: 0.8527, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7747/10000, Train Loss: 1.0682, Train Accuracy: 0.8371, Val Loss: 1.1820, Val Accuracy: 0.7232
Epoch 7748/10000, Train Loss: 1.0745, Train Accuracy: 0.8359, Val Loss: 1.1818, Val Accuracy: 0.7232
Epoch 7749/10000, Train Loss: 1.0612, Train Accuracy: 0.8538, Val Loss: 1.1819, Val Accuracy: 0.7277
Epoch 7750/10000, Train Loss: 1.0619, Train Accuracy: 0.8560, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7751/10000, Train Loss: 1.0670, Train Accuracy: 0.8493, Val Loss: 1.1818, Val Accuracy: 0.7277
Epoch 7752/10000, Train Loss: 1.0714, Train Accuracy: 0.8482, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7753/10000, Train Loss: 1.0704, Train Accuracy: 0.8415, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7754/10000, Train Loss: 1.0616, Train Accuracy: 0.8415, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7755/10000, Train Loss: 1.0696, Train Accuracy: 0.8438, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7756/10000, Train Loss: 1.0596, Train Accuracy: 0.8516, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7757/10000, Train Loss: 1.0803, Train Accuracy: 0.8281, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7758/10000, Train Loss: 1.0712, Train Accuracy: 0.8393, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7759/10000, Train Loss: 1.0764, Train Accuracy: 0.8371, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7760/10000, Train Loss: 1.0715, Train Accuracy: 0.8460, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7761/10000, Train Loss: 1.0647, Train Accuracy: 0.8426, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7762/10000, Train Loss: 1.0667, Train Accuracy: 0.8438, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7763/10000, Train Loss: 1.0643, Train Accuracy: 0.8449, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7764/10000, Train Loss: 1.0624, Train Accuracy: 0.8504, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7765/10000, Train Loss: 1.0589, Train Accuracy: 0.8571, Val Loss: 1.1816, Val Accuracy: 0.7277
Epoch 7766/10000, Train Loss: 1.0602, Train Accuracy: 0.8527, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7767/10000, Train Loss: 1.0649, Train Accuracy: 0.8493, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7768/10000, Train Loss: 1.0708, Train Accuracy: 0.8359, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7769/10000, Train Loss: 1.0779, Train Accuracy: 0.8237, Val Loss: 1.1809, Val Accuracy: 0.7232
Epoch 7770/10000, Train Loss: 1.0750, Train Accuracy: 0.8359, Val Loss: 1.1811, Val Accuracy: 0.7232
Epoch 7771/10000, Train Loss: 1.0699, Train Accuracy: 0.8449, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7772/10000, Train Loss: 1.0536, Train Accuracy: 0.8638, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7773/10000, Train Loss: 1.0652, Train Accuracy: 0.8438, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7774/10000, Train Loss: 1.0681, Train Accuracy: 0.8426, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7775/10000, Train Loss: 1.0603, Train Accuracy: 0.8482, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7776/10000, Train Loss: 1.0530, Train Accuracy: 0.8638, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7777/10000, Train Loss: 1.0671, Train Accuracy: 0.8415, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7778/10000, Train Loss: 1.0766, Train Accuracy: 0.8304, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7779/10000, Train Loss: 1.0731, Train Accuracy: 0.8371, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7780/10000, Train Loss: 1.0671, Train Accuracy: 0.8460, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7781/10000, Train Loss: 1.0725, Train Accuracy: 0.8460, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7782/10000, Train Loss: 1.0731, Train Accuracy: 0.8382, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7783/10000, Train Loss: 1.0709, Train Accuracy: 0.8460, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7784/10000, Train Loss: 1.0651, Train Accuracy: 0.8460, Val Loss: 1.1814, Val Accuracy: 0.7277
Epoch 7785/10000, Train Loss: 1.0664, Train Accuracy: 0.8482, Val Loss: 1.1813, Val Accuracy: 0.7277
Epoch 7786/10000, Train Loss: 1.0725, Train Accuracy: 0.8426, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7787/10000, Train Loss: 1.0657, Train Accuracy: 0.8449, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7788/10000, Train Loss: 1.0729, Train Accuracy: 0.8382, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7789/10000, Train Loss: 1.0496, Train Accuracy: 0.8683, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7790/10000, Train Loss: 1.0672, Train Accuracy: 0.8460, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7791/10000, Train Loss: 1.0584, Train Accuracy: 0.8571, Val Loss: 1.1812, Val Accuracy: 0.7277
Epoch 7792/10000, Train Loss: 1.0569, Train Accuracy: 0.8594, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7793/10000, Train Loss: 1.0822, Train Accuracy: 0.8292, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7794/10000, Train Loss: 1.0708, Train Accuracy: 0.8449, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7795/10000, Train Loss: 1.0663, Train Accuracy: 0.8438, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7796/10000, Train Loss: 1.0791, Train Accuracy: 0.8315, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7797/10000, Train Loss: 1.0786, Train Accuracy: 0.8259, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7798/10000, Train Loss: 1.0633, Train Accuracy: 0.8538, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7799/10000, Train Loss: 1.0626, Train Accuracy: 0.8527, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7800/10000, Train Loss: 1.0626, Train Accuracy: 0.8415, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7801/10000, Train Loss: 1.0782, Train Accuracy: 0.8337, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7802/10000, Train Loss: 1.0743, Train Accuracy: 0.8393, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7803/10000, Train Loss: 1.0789, Train Accuracy: 0.8304, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7804/10000, Train Loss: 1.0714, Train Accuracy: 0.8415, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7805/10000, Train Loss: 1.0665, Train Accuracy: 0.8426, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7806/10000, Train Loss: 1.0649, Train Accuracy: 0.8527, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7807/10000, Train Loss: 1.0577, Train Accuracy: 0.8493, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7808/10000, Train Loss: 1.0675, Train Accuracy: 0.8449, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7809/10000, Train Loss: 1.0631, Train Accuracy: 0.8527, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7810/10000, Train Loss: 1.0726, Train Accuracy: 0.8404, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7811/10000, Train Loss: 1.0579, Train Accuracy: 0.8527, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7812/10000, Train Loss: 1.0636, Train Accuracy: 0.8504, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7813/10000, Train Loss: 1.0661, Train Accuracy: 0.8549, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7814/10000, Train Loss: 1.0780, Train Accuracy: 0.8337, Val Loss: 1.1807, Val Accuracy: 0.7277
Epoch 7815/10000, Train Loss: 1.0696, Train Accuracy: 0.8404, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7816/10000, Train Loss: 1.0697, Train Accuracy: 0.8449, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7817/10000, Train Loss: 1.0626, Train Accuracy: 0.8482, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7818/10000, Train Loss: 1.0620, Train Accuracy: 0.8504, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7819/10000, Train Loss: 1.0692, Train Accuracy: 0.8426, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7820/10000, Train Loss: 1.0637, Train Accuracy: 0.8516, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7821/10000, Train Loss: 1.0667, Train Accuracy: 0.8571, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7822/10000, Train Loss: 1.0502, Train Accuracy: 0.8605, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7823/10000, Train Loss: 1.0654, Train Accuracy: 0.8482, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7824/10000, Train Loss: 1.0717, Train Accuracy: 0.8438, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7825/10000, Train Loss: 1.0813, Train Accuracy: 0.8292, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7826/10000, Train Loss: 1.0603, Train Accuracy: 0.8493, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7827/10000, Train Loss: 1.0673, Train Accuracy: 0.8449, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7828/10000, Train Loss: 1.0646, Train Accuracy: 0.8504, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7829/10000, Train Loss: 1.0719, Train Accuracy: 0.8415, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7830/10000, Train Loss: 1.0682, Train Accuracy: 0.8482, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7831/10000, Train Loss: 1.0696, Train Accuracy: 0.8404, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7832/10000, Train Loss: 1.0655, Train Accuracy: 0.8527, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7833/10000, Train Loss: 1.0667, Train Accuracy: 0.8393, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7834/10000, Train Loss: 1.0611, Train Accuracy: 0.8493, Val Loss: 1.1793, Val Accuracy: 0.7277
Epoch 7835/10000, Train Loss: 1.0706, Train Accuracy: 0.8438, Val Loss: 1.1791, Val Accuracy: 0.7277
Epoch 7836/10000, Train Loss: 1.0607, Train Accuracy: 0.8527, Val Loss: 1.1790, Val Accuracy: 0.7277
Epoch 7837/10000, Train Loss: 1.0614, Train Accuracy: 0.8493, Val Loss: 1.1791, Val Accuracy: 0.7277
Epoch 7838/10000, Train Loss: 1.0570, Train Accuracy: 0.8560, Val Loss: 1.1792, Val Accuracy: 0.7321
Epoch 7839/10000, Train Loss: 1.0557, Train Accuracy: 0.8560, Val Loss: 1.1792, Val Accuracy: 0.7277
Epoch 7840/10000, Train Loss: 1.0745, Train Accuracy: 0.8359, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7841/10000, Train Loss: 1.0636, Train Accuracy: 0.8471, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7842/10000, Train Loss: 1.0702, Train Accuracy: 0.8393, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7843/10000, Train Loss: 1.0704, Train Accuracy: 0.8348, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7844/10000, Train Loss: 1.0718, Train Accuracy: 0.8393, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7845/10000, Train Loss: 1.0699, Train Accuracy: 0.8426, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7846/10000, Train Loss: 1.0629, Train Accuracy: 0.8438, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7847/10000, Train Loss: 1.0611, Train Accuracy: 0.8516, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7848/10000, Train Loss: 1.0745, Train Accuracy: 0.8371, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7849/10000, Train Loss: 1.0728, Train Accuracy: 0.8438, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7850/10000, Train Loss: 1.0657, Train Accuracy: 0.8471, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7851/10000, Train Loss: 1.0573, Train Accuracy: 0.8527, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7852/10000, Train Loss: 1.0666, Train Accuracy: 0.8449, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7853/10000, Train Loss: 1.0664, Train Accuracy: 0.8471, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7854/10000, Train Loss: 1.0724, Train Accuracy: 0.8326, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7855/10000, Train Loss: 1.0590, Train Accuracy: 0.8549, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7856/10000, Train Loss: 1.0566, Train Accuracy: 0.8594, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7857/10000, Train Loss: 1.0738, Train Accuracy: 0.8304, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7858/10000, Train Loss: 1.0723, Train Accuracy: 0.8371, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7859/10000, Train Loss: 1.0478, Train Accuracy: 0.8616, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7860/10000, Train Loss: 1.0667, Train Accuracy: 0.8438, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7861/10000, Train Loss: 1.0676, Train Accuracy: 0.8393, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7862/10000, Train Loss: 1.0608, Train Accuracy: 0.8527, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7863/10000, Train Loss: 1.0744, Train Accuracy: 0.8348, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7864/10000, Train Loss: 1.0518, Train Accuracy: 0.8594, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7865/10000, Train Loss: 1.0528, Train Accuracy: 0.8661, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7866/10000, Train Loss: 1.0773, Train Accuracy: 0.8292, Val Loss: 1.1796, Val Accuracy: 0.7277
Epoch 7867/10000, Train Loss: 1.0601, Train Accuracy: 0.8538, Val Loss: 1.1796, Val Accuracy: 0.7277
Epoch 7868/10000, Train Loss: 1.0558, Train Accuracy: 0.8605, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7869/10000, Train Loss: 1.0680, Train Accuracy: 0.8471, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7870/10000, Train Loss: 1.0722, Train Accuracy: 0.8348, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7871/10000, Train Loss: 1.0640, Train Accuracy: 0.8415, Val Loss: 1.1792, Val Accuracy: 0.7277
Epoch 7872/10000, Train Loss: 1.0743, Train Accuracy: 0.8348, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7873/10000, Train Loss: 1.0523, Train Accuracy: 0.8616, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7874/10000, Train Loss: 1.0659, Train Accuracy: 0.8482, Val Loss: 1.1793, Val Accuracy: 0.7277
Epoch 7875/10000, Train Loss: 1.0726, Train Accuracy: 0.8382, Val Loss: 1.1791, Val Accuracy: 0.7277
Epoch 7876/10000, Train Loss: 1.0650, Train Accuracy: 0.8482, Val Loss: 1.1791, Val Accuracy: 0.7277
Epoch 7877/10000, Train Loss: 1.0627, Train Accuracy: 0.8493, Val Loss: 1.1791, Val Accuracy: 0.7277
Epoch 7878/10000, Train Loss: 1.0571, Train Accuracy: 0.8538, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7879/10000, Train Loss: 1.0568, Train Accuracy: 0.8471, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7880/10000, Train Loss: 1.0644, Train Accuracy: 0.8460, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7881/10000, Train Loss: 1.0628, Train Accuracy: 0.8493, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7882/10000, Train Loss: 1.0665, Train Accuracy: 0.8471, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7883/10000, Train Loss: 1.0555, Train Accuracy: 0.8650, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7884/10000, Train Loss: 1.0687, Train Accuracy: 0.8404, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7885/10000, Train Loss: 1.0635, Train Accuracy: 0.8460, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7886/10000, Train Loss: 1.0500, Train Accuracy: 0.8694, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7887/10000, Train Loss: 1.0718, Train Accuracy: 0.8337, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7888/10000, Train Loss: 1.0633, Train Accuracy: 0.8460, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7889/10000, Train Loss: 1.0613, Train Accuracy: 0.8460, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7890/10000, Train Loss: 1.0698, Train Accuracy: 0.8315, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7891/10000, Train Loss: 1.0519, Train Accuracy: 0.8638, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7892/10000, Train Loss: 1.0713, Train Accuracy: 0.8382, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7893/10000, Train Loss: 1.0635, Train Accuracy: 0.8460, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7894/10000, Train Loss: 1.0728, Train Accuracy: 0.8337, Val Loss: 1.1796, Val Accuracy: 0.7277
Epoch 7895/10000, Train Loss: 1.0554, Train Accuracy: 0.8605, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7896/10000, Train Loss: 1.0687, Train Accuracy: 0.8482, Val Loss: 1.1794, Val Accuracy: 0.7277
Epoch 7897/10000, Train Loss: 1.0719, Train Accuracy: 0.8449, Val Loss: 1.1795, Val Accuracy: 0.7277
Epoch 7898/10000, Train Loss: 1.0712, Train Accuracy: 0.8438, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7899/10000, Train Loss: 1.0650, Train Accuracy: 0.8594, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7900/10000, Train Loss: 1.0641, Train Accuracy: 0.8426, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7901/10000, Train Loss: 1.0615, Train Accuracy: 0.8527, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7902/10000, Train Loss: 1.0731, Train Accuracy: 0.8382, Val Loss: 1.1793, Val Accuracy: 0.7277
Epoch 7903/10000, Train Loss: 1.0681, Train Accuracy: 0.8449, Val Loss: 1.1796, Val Accuracy: 0.7277
Epoch 7904/10000, Train Loss: 1.0669, Train Accuracy: 0.8471, Val Loss: 1.1797, Val Accuracy: 0.7277
Epoch 7905/10000, Train Loss: 1.0615, Train Accuracy: 0.8393, Val Loss: 1.1798, Val Accuracy: 0.7277
Epoch 7906/10000, Train Loss: 1.0565, Train Accuracy: 0.8527, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7907/10000, Train Loss: 1.0615, Train Accuracy: 0.8616, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7908/10000, Train Loss: 1.0586, Train Accuracy: 0.8560, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7909/10000, Train Loss: 1.0674, Train Accuracy: 0.8438, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7910/10000, Train Loss: 1.0610, Train Accuracy: 0.8549, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7911/10000, Train Loss: 1.0631, Train Accuracy: 0.8460, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7912/10000, Train Loss: 1.0752, Train Accuracy: 0.8315, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7913/10000, Train Loss: 1.0585, Train Accuracy: 0.8571, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7914/10000, Train Loss: 1.0691, Train Accuracy: 0.8438, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7915/10000, Train Loss: 1.0667, Train Accuracy: 0.8415, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7916/10000, Train Loss: 1.0605, Train Accuracy: 0.8493, Val Loss: 1.1811, Val Accuracy: 0.7277
Epoch 7917/10000, Train Loss: 1.0586, Train Accuracy: 0.8571, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7918/10000, Train Loss: 1.0763, Train Accuracy: 0.8371, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7919/10000, Train Loss: 1.0656, Train Accuracy: 0.8460, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7920/10000, Train Loss: 1.0582, Train Accuracy: 0.8527, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7921/10000, Train Loss: 1.0656, Train Accuracy: 0.8504, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7922/10000, Train Loss: 1.0617, Train Accuracy: 0.8538, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7923/10000, Train Loss: 1.0725, Train Accuracy: 0.8348, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7924/10000, Train Loss: 1.0544, Train Accuracy: 0.8650, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7925/10000, Train Loss: 1.0550, Train Accuracy: 0.8605, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7926/10000, Train Loss: 1.0673, Train Accuracy: 0.8415, Val Loss: 1.1806, Val Accuracy: 0.7277
Epoch 7927/10000, Train Loss: 1.0717, Train Accuracy: 0.8426, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7928/10000, Train Loss: 1.0431, Train Accuracy: 0.8739, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7929/10000, Train Loss: 1.0583, Train Accuracy: 0.8571, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7930/10000, Train Loss: 1.0698, Train Accuracy: 0.8404, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7931/10000, Train Loss: 1.0650, Train Accuracy: 0.8438, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 7932/10000, Train Loss: 1.0630, Train Accuracy: 0.8460, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7933/10000, Train Loss: 1.0686, Train Accuracy: 0.8438, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7934/10000, Train Loss: 1.0773, Train Accuracy: 0.8337, Val Loss: 1.1803, Val Accuracy: 0.7277
Epoch 7935/10000, Train Loss: 1.0643, Train Accuracy: 0.8482, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7936/10000, Train Loss: 1.0637, Train Accuracy: 0.8460, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7937/10000, Train Loss: 1.0685, Train Accuracy: 0.8426, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7938/10000, Train Loss: 1.0668, Train Accuracy: 0.8449, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7939/10000, Train Loss: 1.0635, Train Accuracy: 0.8516, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7940/10000, Train Loss: 1.0590, Train Accuracy: 0.8571, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7941/10000, Train Loss: 1.0608, Train Accuracy: 0.8527, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7942/10000, Train Loss: 1.0590, Train Accuracy: 0.8594, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7943/10000, Train Loss: 1.0768, Train Accuracy: 0.8270, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7944/10000, Train Loss: 1.0629, Train Accuracy: 0.8504, Val Loss: 1.1799, Val Accuracy: 0.7277
Epoch 7945/10000, Train Loss: 1.0749, Train Accuracy: 0.8359, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7946/10000, Train Loss: 1.0556, Train Accuracy: 0.8605, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 7947/10000, Train Loss: 1.0499, Train Accuracy: 0.8638, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 7948/10000, Train Loss: 1.0835, Train Accuracy: 0.8270, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7949/10000, Train Loss: 1.0598, Train Accuracy: 0.8516, Val Loss: 1.1802, Val Accuracy: 0.7321
Epoch 7950/10000, Train Loss: 1.0605, Train Accuracy: 0.8516, Val Loss: 1.1800, Val Accuracy: 0.7321
Epoch 7951/10000, Train Loss: 1.0779, Train Accuracy: 0.8382, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7952/10000, Train Loss: 1.0766, Train Accuracy: 0.8292, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 7953/10000, Train Loss: 1.0548, Train Accuracy: 0.8549, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7954/10000, Train Loss: 1.0660, Train Accuracy: 0.8460, Val Loss: 1.1805, Val Accuracy: 0.7321
Epoch 7955/10000, Train Loss: 1.0568, Train Accuracy: 0.8516, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7956/10000, Train Loss: 1.0749, Train Accuracy: 0.8359, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7957/10000, Train Loss: 1.0612, Train Accuracy: 0.8471, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7958/10000, Train Loss: 1.0731, Train Accuracy: 0.8382, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7959/10000, Train Loss: 1.0678, Train Accuracy: 0.8438, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7960/10000, Train Loss: 1.0644, Train Accuracy: 0.8471, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 7961/10000, Train Loss: 1.0503, Train Accuracy: 0.8683, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 7962/10000, Train Loss: 1.0757, Train Accuracy: 0.8326, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7963/10000, Train Loss: 1.0616, Train Accuracy: 0.8516, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7964/10000, Train Loss: 1.0628, Train Accuracy: 0.8471, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7965/10000, Train Loss: 1.0722, Train Accuracy: 0.8348, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7966/10000, Train Loss: 1.0653, Train Accuracy: 0.8449, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7967/10000, Train Loss: 1.0639, Train Accuracy: 0.8471, Val Loss: 1.1805, Val Accuracy: 0.7321
Epoch 7968/10000, Train Loss: 1.0458, Train Accuracy: 0.8694, Val Loss: 1.1806, Val Accuracy: 0.7321
Epoch 7969/10000, Train Loss: 1.0681, Train Accuracy: 0.8504, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7970/10000, Train Loss: 1.0701, Train Accuracy: 0.8438, Val Loss: 1.1805, Val Accuracy: 0.7321
Epoch 7971/10000, Train Loss: 1.0477, Train Accuracy: 0.8728, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7972/10000, Train Loss: 1.0582, Train Accuracy: 0.8493, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7973/10000, Train Loss: 1.0596, Train Accuracy: 0.8471, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7974/10000, Train Loss: 1.0623, Train Accuracy: 0.8482, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7975/10000, Train Loss: 1.0578, Train Accuracy: 0.8527, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7976/10000, Train Loss: 1.0636, Train Accuracy: 0.8516, Val Loss: 1.1802, Val Accuracy: 0.7321
Epoch 7977/10000, Train Loss: 1.0727, Train Accuracy: 0.8393, Val Loss: 1.1805, Val Accuracy: 0.7321
Epoch 7978/10000, Train Loss: 1.0673, Train Accuracy: 0.8426, Val Loss: 1.1808, Val Accuracy: 0.7321
Epoch 7979/10000, Train Loss: 1.0672, Train Accuracy: 0.8371, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7980/10000, Train Loss: 1.0583, Train Accuracy: 0.8583, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7981/10000, Train Loss: 1.0630, Train Accuracy: 0.8460, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7982/10000, Train Loss: 1.0630, Train Accuracy: 0.8504, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7983/10000, Train Loss: 1.0714, Train Accuracy: 0.8415, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7984/10000, Train Loss: 1.0479, Train Accuracy: 0.8650, Val Loss: 1.1809, Val Accuracy: 0.7277
Epoch 7985/10000, Train Loss: 1.0642, Train Accuracy: 0.8527, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7986/10000, Train Loss: 1.0585, Train Accuracy: 0.8404, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7987/10000, Train Loss: 1.0603, Train Accuracy: 0.8516, Val Loss: 1.1810, Val Accuracy: 0.7277
Epoch 7988/10000, Train Loss: 1.0729, Train Accuracy: 0.8404, Val Loss: 1.1808, Val Accuracy: 0.7277
Epoch 7989/10000, Train Loss: 1.0695, Train Accuracy: 0.8449, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 7990/10000, Train Loss: 1.0642, Train Accuracy: 0.8504, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7991/10000, Train Loss: 1.0690, Train Accuracy: 0.8449, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7992/10000, Train Loss: 1.0545, Train Accuracy: 0.8616, Val Loss: 1.1806, Val Accuracy: 0.7321
Epoch 7993/10000, Train Loss: 1.0656, Train Accuracy: 0.8504, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7994/10000, Train Loss: 1.0651, Train Accuracy: 0.8493, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 7995/10000, Train Loss: 1.0707, Train Accuracy: 0.8393, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 7996/10000, Train Loss: 1.0575, Train Accuracy: 0.8538, Val Loss: 1.1800, Val Accuracy: 0.7321
Epoch 7997/10000, Train Loss: 1.0648, Train Accuracy: 0.8471, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 7998/10000, Train Loss: 1.0704, Train Accuracy: 0.8415, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 7999/10000, Train Loss: 1.0532, Train Accuracy: 0.8616, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 8000/10000, Train Loss: 1.0541, Train Accuracy: 0.8571, Val Loss: 1.1803, Val Accuracy: 0.7321
Epoch 8001/10000, Train Loss: 1.0528, Train Accuracy: 0.8594, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 8002/10000, Train Loss: 1.0569, Train Accuracy: 0.8560, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 8003/10000, Train Loss: 1.0570, Train Accuracy: 0.8616, Val Loss: 1.1804, Val Accuracy: 0.7321
Epoch 8004/10000, Train Loss: 1.0562, Train Accuracy: 0.8583, Val Loss: 1.1805, Val Accuracy: 0.7277
Epoch 8005/10000, Train Loss: 1.0577, Train Accuracy: 0.8583, Val Loss: 1.1804, Val Accuracy: 0.7277
Epoch 8006/10000, Train Loss: 1.0654, Train Accuracy: 0.8471, Val Loss: 1.1802, Val Accuracy: 0.7277
Epoch 8007/10000, Train Loss: 1.0611, Train Accuracy: 0.8449, Val Loss: 1.1800, Val Accuracy: 0.7321
Epoch 8008/10000, Train Loss: 1.0714, Train Accuracy: 0.8438, Val Loss: 1.1800, Val Accuracy: 0.7277
Epoch 8009/10000, Train Loss: 1.0578, Train Accuracy: 0.8538, Val Loss: 1.1799, Val Accuracy: 0.7321
Epoch 8010/10000, Train Loss: 1.0678, Train Accuracy: 0.8460, Val Loss: 1.1801, Val Accuracy: 0.7321
Epoch 8011/10000, Train Loss: 1.0623, Train Accuracy: 0.8516, Val Loss: 1.1801, Val Accuracy: 0.7277
Epoch 8012/10000, Train Loss: 1.0620, Train Accuracy: 0.8471, Val Loss: 1.1800, Val Accuracy: 0.7321
Epoch 8013/10000, Train Loss: 1.0522, Train Accuracy: 0.8549, Val Loss: 1.1799, Val Accuracy: 0.7366
Epoch 8014/10000, Train Loss: 1.0707, Train Accuracy: 0.8393, Val Loss: 1.1797, Val Accuracy: 0.7321
Epoch 8015/10000, Train Loss: 1.0595, Train Accuracy: 0.8438, Val Loss: 1.1795, Val Accuracy: 0.7366
Epoch 8016/10000, Train Loss: 1.0537, Train Accuracy: 0.8594, Val Loss: 1.1796, Val Accuracy: 0.7321
Epoch 8017/10000, Train Loss: 1.0660, Train Accuracy: 0.8516, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8018/10000, Train Loss: 1.0587, Train Accuracy: 0.8527, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8019/10000, Train Loss: 1.0683, Train Accuracy: 0.8460, Val Loss: 1.1794, Val Accuracy: 0.7321
Epoch 8020/10000, Train Loss: 1.0714, Train Accuracy: 0.8438, Val Loss: 1.1794, Val Accuracy: 0.7366
Epoch 8021/10000, Train Loss: 1.0726, Train Accuracy: 0.8404, Val Loss: 1.1793, Val Accuracy: 0.7366
Epoch 8022/10000, Train Loss: 1.0561, Train Accuracy: 0.8616, Val Loss: 1.1796, Val Accuracy: 0.7321
Epoch 8023/10000, Train Loss: 1.0700, Train Accuracy: 0.8415, Val Loss: 1.1794, Val Accuracy: 0.7321
Epoch 8024/10000, Train Loss: 1.0486, Train Accuracy: 0.8705, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8025/10000, Train Loss: 1.0667, Train Accuracy: 0.8449, Val Loss: 1.1796, Val Accuracy: 0.7366
Epoch 8026/10000, Train Loss: 1.0494, Train Accuracy: 0.8627, Val Loss: 1.1793, Val Accuracy: 0.7366
Epoch 8027/10000, Train Loss: 1.0607, Train Accuracy: 0.8438, Val Loss: 1.1794, Val Accuracy: 0.7366
Epoch 8028/10000, Train Loss: 1.0508, Train Accuracy: 0.8583, Val Loss: 1.1793, Val Accuracy: 0.7366
Epoch 8029/10000, Train Loss: 1.0612, Train Accuracy: 0.8516, Val Loss: 1.1793, Val Accuracy: 0.7366
Epoch 8030/10000, Train Loss: 1.0551, Train Accuracy: 0.8594, Val Loss: 1.1795, Val Accuracy: 0.7366
Epoch 8031/10000, Train Loss: 1.0541, Train Accuracy: 0.8627, Val Loss: 1.1796, Val Accuracy: 0.7366
Epoch 8032/10000, Train Loss: 1.0641, Train Accuracy: 0.8471, Val Loss: 1.1796, Val Accuracy: 0.7321
Epoch 8033/10000, Train Loss: 1.0631, Train Accuracy: 0.8438, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8034/10000, Train Loss: 1.0673, Train Accuracy: 0.8449, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8035/10000, Train Loss: 1.0615, Train Accuracy: 0.8504, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8036/10000, Train Loss: 1.0519, Train Accuracy: 0.8538, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8037/10000, Train Loss: 1.0613, Train Accuracy: 0.8516, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8038/10000, Train Loss: 1.0575, Train Accuracy: 0.8516, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8039/10000, Train Loss: 1.0600, Train Accuracy: 0.8583, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8040/10000, Train Loss: 1.0653, Train Accuracy: 0.8415, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8041/10000, Train Loss: 1.0563, Train Accuracy: 0.8594, Val Loss: 1.1787, Val Accuracy: 0.7321
Epoch 8042/10000, Train Loss: 1.0515, Train Accuracy: 0.8549, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8043/10000, Train Loss: 1.0510, Train Accuracy: 0.8583, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8044/10000, Train Loss: 1.0775, Train Accuracy: 0.8382, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8045/10000, Train Loss: 1.0603, Train Accuracy: 0.8482, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8046/10000, Train Loss: 1.0647, Train Accuracy: 0.8438, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8047/10000, Train Loss: 1.0541, Train Accuracy: 0.8583, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8048/10000, Train Loss: 1.0444, Train Accuracy: 0.8683, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8049/10000, Train Loss: 1.0594, Train Accuracy: 0.8504, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8050/10000, Train Loss: 1.0520, Train Accuracy: 0.8661, Val Loss: 1.1790, Val Accuracy: 0.7366
Epoch 8051/10000, Train Loss: 1.0589, Train Accuracy: 0.8571, Val Loss: 1.1790, Val Accuracy: 0.7366
Epoch 8052/10000, Train Loss: 1.0534, Train Accuracy: 0.8594, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8053/10000, Train Loss: 1.0635, Train Accuracy: 0.8471, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8054/10000, Train Loss: 1.0656, Train Accuracy: 0.8471, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8055/10000, Train Loss: 1.0570, Train Accuracy: 0.8583, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8056/10000, Train Loss: 1.0648, Train Accuracy: 0.8460, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8057/10000, Train Loss: 1.0683, Train Accuracy: 0.8415, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8058/10000, Train Loss: 1.0632, Train Accuracy: 0.8471, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8059/10000, Train Loss: 1.0588, Train Accuracy: 0.8482, Val Loss: 1.1794, Val Accuracy: 0.7366
Epoch 8060/10000, Train Loss: 1.0653, Train Accuracy: 0.8460, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8061/10000, Train Loss: 1.0550, Train Accuracy: 0.8516, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8062/10000, Train Loss: 1.0453, Train Accuracy: 0.8683, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8063/10000, Train Loss: 1.0556, Train Accuracy: 0.8516, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8064/10000, Train Loss: 1.0620, Train Accuracy: 0.8460, Val Loss: 1.1787, Val Accuracy: 0.7366
Epoch 8065/10000, Train Loss: 1.0694, Train Accuracy: 0.8426, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8066/10000, Train Loss: 1.0708, Train Accuracy: 0.8337, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8067/10000, Train Loss: 1.0543, Train Accuracy: 0.8672, Val Loss: 1.1782, Val Accuracy: 0.7366
Epoch 8068/10000, Train Loss: 1.0474, Train Accuracy: 0.8705, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8069/10000, Train Loss: 1.0575, Train Accuracy: 0.8482, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8070/10000, Train Loss: 1.0588, Train Accuracy: 0.8538, Val Loss: 1.1782, Val Accuracy: 0.7366
Epoch 8071/10000, Train Loss: 1.0620, Train Accuracy: 0.8482, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8072/10000, Train Loss: 1.0578, Train Accuracy: 0.8538, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8073/10000, Train Loss: 1.0532, Train Accuracy: 0.8549, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8074/10000, Train Loss: 1.0558, Train Accuracy: 0.8594, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8075/10000, Train Loss: 1.0621, Train Accuracy: 0.8516, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8076/10000, Train Loss: 1.0540, Train Accuracy: 0.8583, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8077/10000, Train Loss: 1.0675, Train Accuracy: 0.8482, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8078/10000, Train Loss: 1.0630, Train Accuracy: 0.8393, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8079/10000, Train Loss: 1.0501, Train Accuracy: 0.8571, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8080/10000, Train Loss: 1.0520, Train Accuracy: 0.8605, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8081/10000, Train Loss: 1.0579, Train Accuracy: 0.8538, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8082/10000, Train Loss: 1.0517, Train Accuracy: 0.8583, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8083/10000, Train Loss: 1.0644, Train Accuracy: 0.8482, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8084/10000, Train Loss: 1.0526, Train Accuracy: 0.8616, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8085/10000, Train Loss: 1.0511, Train Accuracy: 0.8594, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8086/10000, Train Loss: 1.0419, Train Accuracy: 0.8705, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8087/10000, Train Loss: 1.0599, Train Accuracy: 0.8516, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8088/10000, Train Loss: 1.0640, Train Accuracy: 0.8538, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8089/10000, Train Loss: 1.0485, Train Accuracy: 0.8717, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8090/10000, Train Loss: 1.0582, Train Accuracy: 0.8583, Val Loss: 1.1786, Val Accuracy: 0.7321
Epoch 8091/10000, Train Loss: 1.0611, Train Accuracy: 0.8538, Val Loss: 1.1787, Val Accuracy: 0.7321
Epoch 8092/10000, Train Loss: 1.0529, Train Accuracy: 0.8583, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8093/10000, Train Loss: 1.0556, Train Accuracy: 0.8560, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8094/10000, Train Loss: 1.0705, Train Accuracy: 0.8404, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8095/10000, Train Loss: 1.0481, Train Accuracy: 0.8638, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8096/10000, Train Loss: 1.0623, Train Accuracy: 0.8516, Val Loss: 1.1789, Val Accuracy: 0.7321
Epoch 8097/10000, Train Loss: 1.0660, Train Accuracy: 0.8482, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8098/10000, Train Loss: 1.0514, Train Accuracy: 0.8650, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8099/10000, Train Loss: 1.0591, Train Accuracy: 0.8516, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8100/10000, Train Loss: 1.0647, Train Accuracy: 0.8415, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8101/10000, Train Loss: 1.0555, Train Accuracy: 0.8549, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8102/10000, Train Loss: 1.0650, Train Accuracy: 0.8482, Val Loss: 1.1796, Val Accuracy: 0.7321
Epoch 8103/10000, Train Loss: 1.0473, Train Accuracy: 0.8650, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8104/10000, Train Loss: 1.0643, Train Accuracy: 0.8471, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8105/10000, Train Loss: 1.0552, Train Accuracy: 0.8605, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8106/10000, Train Loss: 1.0612, Train Accuracy: 0.8493, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8107/10000, Train Loss: 1.0599, Train Accuracy: 0.8571, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8108/10000, Train Loss: 1.0614, Train Accuracy: 0.8504, Val Loss: 1.1795, Val Accuracy: 0.7321
Epoch 8109/10000, Train Loss: 1.0596, Train Accuracy: 0.8460, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8110/10000, Train Loss: 1.0568, Train Accuracy: 0.8583, Val Loss: 1.1793, Val Accuracy: 0.7321
Epoch 8111/10000, Train Loss: 1.0565, Train Accuracy: 0.8527, Val Loss: 1.1792, Val Accuracy: 0.7321
Epoch 8112/10000, Train Loss: 1.0605, Train Accuracy: 0.8482, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8113/10000, Train Loss: 1.0602, Train Accuracy: 0.8527, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8114/10000, Train Loss: 1.0582, Train Accuracy: 0.8571, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8115/10000, Train Loss: 1.0631, Train Accuracy: 0.8549, Val Loss: 1.1791, Val Accuracy: 0.7321
Epoch 8116/10000, Train Loss: 1.0564, Train Accuracy: 0.8583, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8117/10000, Train Loss: 1.0480, Train Accuracy: 0.8650, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8118/10000, Train Loss: 1.0674, Train Accuracy: 0.8426, Val Loss: 1.1788, Val Accuracy: 0.7321
Epoch 8119/10000, Train Loss: 1.0652, Train Accuracy: 0.8449, Val Loss: 1.1786, Val Accuracy: 0.7321
Epoch 8120/10000, Train Loss: 1.0757, Train Accuracy: 0.8315, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8121/10000, Train Loss: 1.0637, Train Accuracy: 0.8493, Val Loss: 1.1787, Val Accuracy: 0.7321
Epoch 8122/10000, Train Loss: 1.0681, Train Accuracy: 0.8504, Val Loss: 1.1787, Val Accuracy: 0.7366
Epoch 8123/10000, Train Loss: 1.0551, Train Accuracy: 0.8583, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8124/10000, Train Loss: 1.0429, Train Accuracy: 0.8761, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8125/10000, Train Loss: 1.0618, Train Accuracy: 0.8560, Val Loss: 1.1790, Val Accuracy: 0.7366
Epoch 8126/10000, Train Loss: 1.0563, Train Accuracy: 0.8482, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8127/10000, Train Loss: 1.0550, Train Accuracy: 0.8627, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8128/10000, Train Loss: 1.0575, Train Accuracy: 0.8616, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8129/10000, Train Loss: 1.0594, Train Accuracy: 0.8493, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8130/10000, Train Loss: 1.0526, Train Accuracy: 0.8594, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8131/10000, Train Loss: 1.0440, Train Accuracy: 0.8672, Val Loss: 1.1794, Val Accuracy: 0.7366
Epoch 8132/10000, Train Loss: 1.0605, Train Accuracy: 0.8516, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8133/10000, Train Loss: 1.0492, Train Accuracy: 0.8650, Val Loss: 1.1792, Val Accuracy: 0.7366
Epoch 8134/10000, Train Loss: 1.0457, Train Accuracy: 0.8739, Val Loss: 1.1790, Val Accuracy: 0.7411
Epoch 8135/10000, Train Loss: 1.0535, Train Accuracy: 0.8583, Val Loss: 1.1790, Val Accuracy: 0.7321
Epoch 8136/10000, Train Loss: 1.0691, Train Accuracy: 0.8482, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8137/10000, Train Loss: 1.0491, Train Accuracy: 0.8683, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8138/10000, Train Loss: 1.0670, Train Accuracy: 0.8415, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8139/10000, Train Loss: 1.0629, Train Accuracy: 0.8438, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8140/10000, Train Loss: 1.0543, Train Accuracy: 0.8538, Val Loss: 1.1787, Val Accuracy: 0.7366
Epoch 8141/10000, Train Loss: 1.0586, Train Accuracy: 0.8560, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8142/10000, Train Loss: 1.0593, Train Accuracy: 0.8560, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8143/10000, Train Loss: 1.0687, Train Accuracy: 0.8471, Val Loss: 1.1791, Val Accuracy: 0.7366
Epoch 8144/10000, Train Loss: 1.0595, Train Accuracy: 0.8538, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8145/10000, Train Loss: 1.0558, Train Accuracy: 0.8583, Val Loss: 1.1789, Val Accuracy: 0.7366
Epoch 8146/10000, Train Loss: 1.0499, Train Accuracy: 0.8672, Val Loss: 1.1784, Val Accuracy: 0.7411
Epoch 8147/10000, Train Loss: 1.0644, Train Accuracy: 0.8460, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8148/10000, Train Loss: 1.0537, Train Accuracy: 0.8638, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8149/10000, Train Loss: 1.0486, Train Accuracy: 0.8728, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8150/10000, Train Loss: 1.0473, Train Accuracy: 0.8694, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8151/10000, Train Loss: 1.0654, Train Accuracy: 0.8460, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8152/10000, Train Loss: 1.0557, Train Accuracy: 0.8583, Val Loss: 1.1783, Val Accuracy: 0.7411
Epoch 8153/10000, Train Loss: 1.0453, Train Accuracy: 0.8728, Val Loss: 1.1780, Val Accuracy: 0.7411
Epoch 8154/10000, Train Loss: 1.0501, Train Accuracy: 0.8694, Val Loss: 1.1777, Val Accuracy: 0.7411
Epoch 8155/10000, Train Loss: 1.0512, Train Accuracy: 0.8616, Val Loss: 1.1780, Val Accuracy: 0.7411
Epoch 8156/10000, Train Loss: 1.0585, Train Accuracy: 0.8516, Val Loss: 1.1781, Val Accuracy: 0.7366
Epoch 8157/10000, Train Loss: 1.0624, Train Accuracy: 0.8404, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8158/10000, Train Loss: 1.0526, Train Accuracy: 0.8638, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8159/10000, Train Loss: 1.0543, Train Accuracy: 0.8672, Val Loss: 1.1778, Val Accuracy: 0.7366
Epoch 8160/10000, Train Loss: 1.0669, Train Accuracy: 0.8359, Val Loss: 1.1774, Val Accuracy: 0.7366
Epoch 8161/10000, Train Loss: 1.0753, Train Accuracy: 0.8292, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8162/10000, Train Loss: 1.0624, Train Accuracy: 0.8538, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8163/10000, Train Loss: 1.0624, Train Accuracy: 0.8504, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8164/10000, Train Loss: 1.0595, Train Accuracy: 0.8482, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8165/10000, Train Loss: 1.0571, Train Accuracy: 0.8538, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8166/10000, Train Loss: 1.0606, Train Accuracy: 0.8471, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8167/10000, Train Loss: 1.0460, Train Accuracy: 0.8605, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8168/10000, Train Loss: 1.0598, Train Accuracy: 0.8538, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8169/10000, Train Loss: 1.0601, Train Accuracy: 0.8460, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8170/10000, Train Loss: 1.0583, Train Accuracy: 0.8438, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8171/10000, Train Loss: 1.0538, Train Accuracy: 0.8516, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8172/10000, Train Loss: 1.0376, Train Accuracy: 0.8717, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8173/10000, Train Loss: 1.0607, Train Accuracy: 0.8538, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8174/10000, Train Loss: 1.0505, Train Accuracy: 0.8616, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8175/10000, Train Loss: 1.0506, Train Accuracy: 0.8661, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8176/10000, Train Loss: 1.0555, Train Accuracy: 0.8571, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8177/10000, Train Loss: 1.0625, Train Accuracy: 0.8471, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8178/10000, Train Loss: 1.0659, Train Accuracy: 0.8460, Val Loss: 1.1768, Val Accuracy: 0.7411
Epoch 8179/10000, Train Loss: 1.0660, Train Accuracy: 0.8415, Val Loss: 1.1770, Val Accuracy: 0.7411
Epoch 8180/10000, Train Loss: 1.0612, Train Accuracy: 0.8538, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8181/10000, Train Loss: 1.0571, Train Accuracy: 0.8549, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8182/10000, Train Loss: 1.0666, Train Accuracy: 0.8404, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8183/10000, Train Loss: 1.0557, Train Accuracy: 0.8538, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8184/10000, Train Loss: 1.0524, Train Accuracy: 0.8694, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8185/10000, Train Loss: 1.0664, Train Accuracy: 0.8449, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8186/10000, Train Loss: 1.0469, Train Accuracy: 0.8594, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8187/10000, Train Loss: 1.0672, Train Accuracy: 0.8359, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8188/10000, Train Loss: 1.0515, Train Accuracy: 0.8571, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8189/10000, Train Loss: 1.0675, Train Accuracy: 0.8393, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8190/10000, Train Loss: 1.0573, Train Accuracy: 0.8571, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8191/10000, Train Loss: 1.0504, Train Accuracy: 0.8571, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8192/10000, Train Loss: 1.0598, Train Accuracy: 0.8504, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8193/10000, Train Loss: 1.0516, Train Accuracy: 0.8594, Val Loss: 1.1774, Val Accuracy: 0.7366
Epoch 8194/10000, Train Loss: 1.0572, Train Accuracy: 0.8527, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8195/10000, Train Loss: 1.0541, Train Accuracy: 0.8538, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8196/10000, Train Loss: 1.0553, Train Accuracy: 0.8571, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8197/10000, Train Loss: 1.0619, Train Accuracy: 0.8493, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8198/10000, Train Loss: 1.0569, Train Accuracy: 0.8516, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8199/10000, Train Loss: 1.0529, Train Accuracy: 0.8627, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8200/10000, Train Loss: 1.0582, Train Accuracy: 0.8560, Val Loss: 1.1778, Val Accuracy: 0.7366
Epoch 8201/10000, Train Loss: 1.0540, Train Accuracy: 0.8616, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8202/10000, Train Loss: 1.0626, Train Accuracy: 0.8560, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8203/10000, Train Loss: 1.0543, Train Accuracy: 0.8627, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8204/10000, Train Loss: 1.0604, Train Accuracy: 0.8493, Val Loss: 1.1781, Val Accuracy: 0.7366
Epoch 8205/10000, Train Loss: 1.0523, Train Accuracy: 0.8605, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8206/10000, Train Loss: 1.0634, Train Accuracy: 0.8504, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8207/10000, Train Loss: 1.0664, Train Accuracy: 0.8382, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8208/10000, Train Loss: 1.0606, Train Accuracy: 0.8583, Val Loss: 1.1778, Val Accuracy: 0.7366
Epoch 8209/10000, Train Loss: 1.0628, Train Accuracy: 0.8404, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8210/10000, Train Loss: 1.0638, Train Accuracy: 0.8516, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8211/10000, Train Loss: 1.0624, Train Accuracy: 0.8504, Val Loss: 1.1781, Val Accuracy: 0.7366
Epoch 8212/10000, Train Loss: 1.0665, Train Accuracy: 0.8460, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8213/10000, Train Loss: 1.0598, Train Accuracy: 0.8538, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8214/10000, Train Loss: 1.0579, Train Accuracy: 0.8594, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8215/10000, Train Loss: 1.0568, Train Accuracy: 0.8538, Val Loss: 1.1782, Val Accuracy: 0.7366
Epoch 8216/10000, Train Loss: 1.0563, Train Accuracy: 0.8549, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8217/10000, Train Loss: 1.0583, Train Accuracy: 0.8504, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8218/10000, Train Loss: 1.0534, Train Accuracy: 0.8571, Val Loss: 1.1784, Val Accuracy: 0.7321
Epoch 8219/10000, Train Loss: 1.0574, Train Accuracy: 0.8471, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8220/10000, Train Loss: 1.0629, Train Accuracy: 0.8449, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8221/10000, Train Loss: 1.0588, Train Accuracy: 0.8583, Val Loss: 1.1782, Val Accuracy: 0.7366
Epoch 8222/10000, Train Loss: 1.0604, Train Accuracy: 0.8504, Val Loss: 1.1781, Val Accuracy: 0.7321
Epoch 8223/10000, Train Loss: 1.0634, Train Accuracy: 0.8426, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8224/10000, Train Loss: 1.0475, Train Accuracy: 0.8661, Val Loss: 1.1778, Val Accuracy: 0.7366
Epoch 8225/10000, Train Loss: 1.0518, Train Accuracy: 0.8627, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8226/10000, Train Loss: 1.0537, Train Accuracy: 0.8549, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8227/10000, Train Loss: 1.0640, Train Accuracy: 0.8504, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8228/10000, Train Loss: 1.0498, Train Accuracy: 0.8605, Val Loss: 1.1781, Val Accuracy: 0.7366
Epoch 8229/10000, Train Loss: 1.0623, Train Accuracy: 0.8549, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8230/10000, Train Loss: 1.0559, Train Accuracy: 0.8638, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8231/10000, Train Loss: 1.0558, Train Accuracy: 0.8605, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8232/10000, Train Loss: 1.0533, Train Accuracy: 0.8627, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8233/10000, Train Loss: 1.0449, Train Accuracy: 0.8694, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8234/10000, Train Loss: 1.0436, Train Accuracy: 0.8616, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8235/10000, Train Loss: 1.0573, Train Accuracy: 0.8516, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8236/10000, Train Loss: 1.0543, Train Accuracy: 0.8594, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8237/10000, Train Loss: 1.0681, Train Accuracy: 0.8449, Val Loss: 1.1787, Val Accuracy: 0.7366
Epoch 8238/10000, Train Loss: 1.0566, Train Accuracy: 0.8571, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8239/10000, Train Loss: 1.0624, Train Accuracy: 0.8471, Val Loss: 1.1788, Val Accuracy: 0.7366
Epoch 8240/10000, Train Loss: 1.0501, Train Accuracy: 0.8638, Val Loss: 1.1786, Val Accuracy: 0.7366
Epoch 8241/10000, Train Loss: 1.0479, Train Accuracy: 0.8661, Val Loss: 1.1785, Val Accuracy: 0.7366
Epoch 8242/10000, Train Loss: 1.0620, Train Accuracy: 0.8527, Val Loss: 1.1784, Val Accuracy: 0.7366
Epoch 8243/10000, Train Loss: 1.0565, Train Accuracy: 0.8538, Val Loss: 1.1783, Val Accuracy: 0.7366
Epoch 8244/10000, Train Loss: 1.0438, Train Accuracy: 0.8705, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8245/10000, Train Loss: 1.0532, Train Accuracy: 0.8560, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8246/10000, Train Loss: 1.0572, Train Accuracy: 0.8560, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8247/10000, Train Loss: 1.0576, Train Accuracy: 0.8493, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8248/10000, Train Loss: 1.0468, Train Accuracy: 0.8661, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8249/10000, Train Loss: 1.0538, Train Accuracy: 0.8583, Val Loss: 1.1781, Val Accuracy: 0.7366
Epoch 8250/10000, Train Loss: 1.0589, Train Accuracy: 0.8516, Val Loss: 1.1780, Val Accuracy: 0.7366
Epoch 8251/10000, Train Loss: 1.0467, Train Accuracy: 0.8694, Val Loss: 1.1779, Val Accuracy: 0.7366
Epoch 8252/10000, Train Loss: 1.0459, Train Accuracy: 0.8672, Val Loss: 1.1780, Val Accuracy: 0.7411
Epoch 8253/10000, Train Loss: 1.0560, Train Accuracy: 0.8583, Val Loss: 1.1784, Val Accuracy: 0.7411
Epoch 8254/10000, Train Loss: 1.0561, Train Accuracy: 0.8538, Val Loss: 1.1785, Val Accuracy: 0.7411
Epoch 8255/10000, Train Loss: 1.0662, Train Accuracy: 0.8538, Val Loss: 1.1785, Val Accuracy: 0.7411
Epoch 8256/10000, Train Loss: 1.0646, Train Accuracy: 0.8404, Val Loss: 1.1784, Val Accuracy: 0.7411
Epoch 8257/10000, Train Loss: 1.0610, Train Accuracy: 0.8560, Val Loss: 1.1781, Val Accuracy: 0.7411
Epoch 8258/10000, Train Loss: 1.0377, Train Accuracy: 0.8772, Val Loss: 1.1780, Val Accuracy: 0.7411
Epoch 8259/10000, Train Loss: 1.0531, Train Accuracy: 0.8605, Val Loss: 1.1780, Val Accuracy: 0.7411
Epoch 8260/10000, Train Loss: 1.0629, Train Accuracy: 0.8560, Val Loss: 1.1776, Val Accuracy: 0.7411
Epoch 8261/10000, Train Loss: 1.0506, Train Accuracy: 0.8616, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8262/10000, Train Loss: 1.0611, Train Accuracy: 0.8482, Val Loss: 1.1776, Val Accuracy: 0.7411
Epoch 8263/10000, Train Loss: 1.0545, Train Accuracy: 0.8571, Val Loss: 1.1777, Val Accuracy: 0.7411
Epoch 8264/10000, Train Loss: 1.0584, Train Accuracy: 0.8504, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8265/10000, Train Loss: 1.0427, Train Accuracy: 0.8694, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8266/10000, Train Loss: 1.0500, Train Accuracy: 0.8627, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8267/10000, Train Loss: 1.0437, Train Accuracy: 0.8705, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8268/10000, Train Loss: 1.0410, Train Accuracy: 0.8705, Val Loss: 1.1776, Val Accuracy: 0.7411
Epoch 8269/10000, Train Loss: 1.0564, Train Accuracy: 0.8504, Val Loss: 1.1774, Val Accuracy: 0.7411
Epoch 8270/10000, Train Loss: 1.0520, Train Accuracy: 0.8705, Val Loss: 1.1773, Val Accuracy: 0.7411
Epoch 8271/10000, Train Loss: 1.0531, Train Accuracy: 0.8538, Val Loss: 1.1774, Val Accuracy: 0.7411
Epoch 8272/10000, Train Loss: 1.0522, Train Accuracy: 0.8616, Val Loss: 1.1773, Val Accuracy: 0.7411
Epoch 8273/10000, Train Loss: 1.0495, Train Accuracy: 0.8638, Val Loss: 1.1773, Val Accuracy: 0.7411
Epoch 8274/10000, Train Loss: 1.0592, Train Accuracy: 0.8527, Val Loss: 1.1773, Val Accuracy: 0.7411
Epoch 8275/10000, Train Loss: 1.0540, Train Accuracy: 0.8571, Val Loss: 1.1775, Val Accuracy: 0.7411
Epoch 8276/10000, Train Loss: 1.0596, Train Accuracy: 0.8460, Val Loss: 1.1774, Val Accuracy: 0.7411
Epoch 8277/10000, Train Loss: 1.0667, Train Accuracy: 0.8493, Val Loss: 1.1772, Val Accuracy: 0.7411
Epoch 8278/10000, Train Loss: 1.0520, Train Accuracy: 0.8560, Val Loss: 1.1771, Val Accuracy: 0.7411
Epoch 8279/10000, Train Loss: 1.0657, Train Accuracy: 0.8382, Val Loss: 1.1770, Val Accuracy: 0.7411
Epoch 8280/10000, Train Loss: 1.0525, Train Accuracy: 0.8594, Val Loss: 1.1770, Val Accuracy: 0.7411
Epoch 8281/10000, Train Loss: 1.0587, Train Accuracy: 0.8482, Val Loss: 1.1767, Val Accuracy: 0.7411
Epoch 8282/10000, Train Loss: 1.0601, Train Accuracy: 0.8549, Val Loss: 1.1768, Val Accuracy: 0.7411
Epoch 8283/10000, Train Loss: 1.0517, Train Accuracy: 0.8560, Val Loss: 1.1768, Val Accuracy: 0.7411
Epoch 8284/10000, Train Loss: 1.0579, Train Accuracy: 0.8583, Val Loss: 1.1767, Val Accuracy: 0.7411
Epoch 8285/10000, Train Loss: 1.0510, Train Accuracy: 0.8638, Val Loss: 1.1768, Val Accuracy: 0.7411
Epoch 8286/10000, Train Loss: 1.0563, Train Accuracy: 0.8583, Val Loss: 1.1766, Val Accuracy: 0.7411
Epoch 8287/10000, Train Loss: 1.0534, Train Accuracy: 0.8627, Val Loss: 1.1766, Val Accuracy: 0.7411
Epoch 8288/10000, Train Loss: 1.0479, Train Accuracy: 0.8650, Val Loss: 1.1767, Val Accuracy: 0.7411
Epoch 8289/10000, Train Loss: 1.0534, Train Accuracy: 0.8583, Val Loss: 1.1769, Val Accuracy: 0.7411
Epoch 8290/10000, Train Loss: 1.0548, Train Accuracy: 0.8627, Val Loss: 1.1767, Val Accuracy: 0.7411
Epoch 8291/10000, Train Loss: 1.0491, Train Accuracy: 0.8694, Val Loss: 1.1768, Val Accuracy: 0.7411
Epoch 8292/10000, Train Loss: 1.0479, Train Accuracy: 0.8650, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8293/10000, Train Loss: 1.0470, Train Accuracy: 0.8650, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8294/10000, Train Loss: 1.0471, Train Accuracy: 0.8661, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8295/10000, Train Loss: 1.0584, Train Accuracy: 0.8616, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8296/10000, Train Loss: 1.0617, Train Accuracy: 0.8538, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8297/10000, Train Loss: 1.0542, Train Accuracy: 0.8638, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8298/10000, Train Loss: 1.0571, Train Accuracy: 0.8605, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8299/10000, Train Loss: 1.0537, Train Accuracy: 0.8560, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8300/10000, Train Loss: 1.0579, Train Accuracy: 0.8549, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8301/10000, Train Loss: 1.0487, Train Accuracy: 0.8627, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8302/10000, Train Loss: 1.0488, Train Accuracy: 0.8638, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8303/10000, Train Loss: 1.0532, Train Accuracy: 0.8616, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8304/10000, Train Loss: 1.0580, Train Accuracy: 0.8538, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8305/10000, Train Loss: 1.0467, Train Accuracy: 0.8672, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8306/10000, Train Loss: 1.0478, Train Accuracy: 0.8638, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8307/10000, Train Loss: 1.0447, Train Accuracy: 0.8750, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8308/10000, Train Loss: 1.0521, Train Accuracy: 0.8594, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8309/10000, Train Loss: 1.0489, Train Accuracy: 0.8672, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8310/10000, Train Loss: 1.0561, Train Accuracy: 0.8560, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8311/10000, Train Loss: 1.0449, Train Accuracy: 0.8728, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8312/10000, Train Loss: 1.0490, Train Accuracy: 0.8594, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8313/10000, Train Loss: 1.0555, Train Accuracy: 0.8560, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8314/10000, Train Loss: 1.0582, Train Accuracy: 0.8560, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8315/10000, Train Loss: 1.0489, Train Accuracy: 0.8717, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8316/10000, Train Loss: 1.0454, Train Accuracy: 0.8661, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8317/10000, Train Loss: 1.0514, Train Accuracy: 0.8661, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8318/10000, Train Loss: 1.0555, Train Accuracy: 0.8583, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8319/10000, Train Loss: 1.0429, Train Accuracy: 0.8638, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8320/10000, Train Loss: 1.0677, Train Accuracy: 0.8449, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8321/10000, Train Loss: 1.0558, Train Accuracy: 0.8527, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8322/10000, Train Loss: 1.0546, Train Accuracy: 0.8638, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8323/10000, Train Loss: 1.0564, Train Accuracy: 0.8583, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8324/10000, Train Loss: 1.0376, Train Accuracy: 0.8772, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8325/10000, Train Loss: 1.0629, Train Accuracy: 0.8493, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8326/10000, Train Loss: 1.0520, Train Accuracy: 0.8571, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8327/10000, Train Loss: 1.0671, Train Accuracy: 0.8359, Val Loss: 1.1774, Val Accuracy: 0.7366
Epoch 8328/10000, Train Loss: 1.0612, Train Accuracy: 0.8504, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8329/10000, Train Loss: 1.0499, Train Accuracy: 0.8661, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8330/10000, Train Loss: 1.0505, Train Accuracy: 0.8605, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8331/10000, Train Loss: 1.0507, Train Accuracy: 0.8627, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8332/10000, Train Loss: 1.0387, Train Accuracy: 0.8728, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8333/10000, Train Loss: 1.0568, Train Accuracy: 0.8583, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8334/10000, Train Loss: 1.0482, Train Accuracy: 0.8661, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8335/10000, Train Loss: 1.0598, Train Accuracy: 0.8527, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8336/10000, Train Loss: 1.0594, Train Accuracy: 0.8493, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8337/10000, Train Loss: 1.0586, Train Accuracy: 0.8549, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8338/10000, Train Loss: 1.0571, Train Accuracy: 0.8583, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8339/10000, Train Loss: 1.0503, Train Accuracy: 0.8594, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8340/10000, Train Loss: 1.0576, Train Accuracy: 0.8560, Val Loss: 1.1762, Val Accuracy: 0.7411
Epoch 8341/10000, Train Loss: 1.0463, Train Accuracy: 0.8560, Val Loss: 1.1762, Val Accuracy: 0.7411
Epoch 8342/10000, Train Loss: 1.0524, Train Accuracy: 0.8594, Val Loss: 1.1764, Val Accuracy: 0.7411
Epoch 8343/10000, Train Loss: 1.0494, Train Accuracy: 0.8538, Val Loss: 1.1763, Val Accuracy: 0.7411
Epoch 8344/10000, Train Loss: 1.0517, Train Accuracy: 0.8549, Val Loss: 1.1764, Val Accuracy: 0.7411
Epoch 8345/10000, Train Loss: 1.0580, Train Accuracy: 0.8504, Val Loss: 1.1761, Val Accuracy: 0.7411
Epoch 8346/10000, Train Loss: 1.0494, Train Accuracy: 0.8616, Val Loss: 1.1758, Val Accuracy: 0.7411
Epoch 8347/10000, Train Loss: 1.0556, Train Accuracy: 0.8605, Val Loss: 1.1758, Val Accuracy: 0.7411
Epoch 8348/10000, Train Loss: 1.0558, Train Accuracy: 0.8571, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 8349/10000, Train Loss: 1.0637, Train Accuracy: 0.8382, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 8350/10000, Train Loss: 1.0523, Train Accuracy: 0.8527, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 8351/10000, Train Loss: 1.0471, Train Accuracy: 0.8694, Val Loss: 1.1758, Val Accuracy: 0.7411
Epoch 8352/10000, Train Loss: 1.0577, Train Accuracy: 0.8504, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 8353/10000, Train Loss: 1.0542, Train Accuracy: 0.8638, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8354/10000, Train Loss: 1.0437, Train Accuracy: 0.8672, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8355/10000, Train Loss: 1.0548, Train Accuracy: 0.8627, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8356/10000, Train Loss: 1.0537, Train Accuracy: 0.8560, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8357/10000, Train Loss: 1.0371, Train Accuracy: 0.8783, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8358/10000, Train Loss: 1.0478, Train Accuracy: 0.8717, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8359/10000, Train Loss: 1.0554, Train Accuracy: 0.8527, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8360/10000, Train Loss: 1.0597, Train Accuracy: 0.8493, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8361/10000, Train Loss: 1.0522, Train Accuracy: 0.8560, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8362/10000, Train Loss: 1.0517, Train Accuracy: 0.8594, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8363/10000, Train Loss: 1.0571, Train Accuracy: 0.8594, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8364/10000, Train Loss: 1.0579, Train Accuracy: 0.8516, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8365/10000, Train Loss: 1.0482, Train Accuracy: 0.8650, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8366/10000, Train Loss: 1.0533, Train Accuracy: 0.8560, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8367/10000, Train Loss: 1.0467, Train Accuracy: 0.8694, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8368/10000, Train Loss: 1.0491, Train Accuracy: 0.8650, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8369/10000, Train Loss: 1.0636, Train Accuracy: 0.8471, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8370/10000, Train Loss: 1.0387, Train Accuracy: 0.8739, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8371/10000, Train Loss: 1.0460, Train Accuracy: 0.8694, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8372/10000, Train Loss: 1.0584, Train Accuracy: 0.8504, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8373/10000, Train Loss: 1.0499, Train Accuracy: 0.8583, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8374/10000, Train Loss: 1.0415, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7411
Epoch 8375/10000, Train Loss: 1.0446, Train Accuracy: 0.8683, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8376/10000, Train Loss: 1.0505, Train Accuracy: 0.8661, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8377/10000, Train Loss: 1.0549, Train Accuracy: 0.8594, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8378/10000, Train Loss: 1.0613, Train Accuracy: 0.8504, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8379/10000, Train Loss: 1.0546, Train Accuracy: 0.8571, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8380/10000, Train Loss: 1.0579, Train Accuracy: 0.8527, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8381/10000, Train Loss: 1.0449, Train Accuracy: 0.8694, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8382/10000, Train Loss: 1.0542, Train Accuracy: 0.8605, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8383/10000, Train Loss: 1.0483, Train Accuracy: 0.8650, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8384/10000, Train Loss: 1.0614, Train Accuracy: 0.8549, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8385/10000, Train Loss: 1.0522, Train Accuracy: 0.8583, Val Loss: 1.1762, Val Accuracy: 0.7411
Epoch 8386/10000, Train Loss: 1.0519, Train Accuracy: 0.8560, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8387/10000, Train Loss: 1.0469, Train Accuracy: 0.8616, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8388/10000, Train Loss: 1.0439, Train Accuracy: 0.8705, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8389/10000, Train Loss: 1.0486, Train Accuracy: 0.8672, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8390/10000, Train Loss: 1.0530, Train Accuracy: 0.8616, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8391/10000, Train Loss: 1.0515, Train Accuracy: 0.8661, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8392/10000, Train Loss: 1.0414, Train Accuracy: 0.8750, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8393/10000, Train Loss: 1.0505, Train Accuracy: 0.8605, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8394/10000, Train Loss: 1.0407, Train Accuracy: 0.8705, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8395/10000, Train Loss: 1.0442, Train Accuracy: 0.8661, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8396/10000, Train Loss: 1.0517, Train Accuracy: 0.8638, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8397/10000, Train Loss: 1.0528, Train Accuracy: 0.8583, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8398/10000, Train Loss: 1.0589, Train Accuracy: 0.8504, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8399/10000, Train Loss: 1.0540, Train Accuracy: 0.8605, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8400/10000, Train Loss: 1.0514, Train Accuracy: 0.8616, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8401/10000, Train Loss: 1.0521, Train Accuracy: 0.8594, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8402/10000, Train Loss: 1.0402, Train Accuracy: 0.8739, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8403/10000, Train Loss: 1.0606, Train Accuracy: 0.8504, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 8404/10000, Train Loss: 1.0420, Train Accuracy: 0.8761, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 8405/10000, Train Loss: 1.0561, Train Accuracy: 0.8605, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8406/10000, Train Loss: 1.0539, Train Accuracy: 0.8616, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8407/10000, Train Loss: 1.0534, Train Accuracy: 0.8538, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8408/10000, Train Loss: 1.0513, Train Accuracy: 0.8627, Val Loss: 1.1752, Val Accuracy: 0.7366
Epoch 8409/10000, Train Loss: 1.0392, Train Accuracy: 0.8761, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8410/10000, Train Loss: 1.0579, Train Accuracy: 0.8493, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8411/10000, Train Loss: 1.0583, Train Accuracy: 0.8482, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8412/10000, Train Loss: 1.0472, Train Accuracy: 0.8638, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8413/10000, Train Loss: 1.0602, Train Accuracy: 0.8471, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8414/10000, Train Loss: 1.0541, Train Accuracy: 0.8605, Val Loss: 1.1752, Val Accuracy: 0.7366
Epoch 8415/10000, Train Loss: 1.0435, Train Accuracy: 0.8694, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8416/10000, Train Loss: 1.0509, Train Accuracy: 0.8516, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 8417/10000, Train Loss: 1.0501, Train Accuracy: 0.8650, Val Loss: 1.1750, Val Accuracy: 0.7411
Epoch 8418/10000, Train Loss: 1.0496, Train Accuracy: 0.8672, Val Loss: 1.1750, Val Accuracy: 0.7411
Epoch 8419/10000, Train Loss: 1.0401, Train Accuracy: 0.8717, Val Loss: 1.1749, Val Accuracy: 0.7411
Epoch 8420/10000, Train Loss: 1.0573, Train Accuracy: 0.8549, Val Loss: 1.1748, Val Accuracy: 0.7411
Epoch 8421/10000, Train Loss: 1.0534, Train Accuracy: 0.8571, Val Loss: 1.1750, Val Accuracy: 0.7455
Epoch 8422/10000, Train Loss: 1.0606, Train Accuracy: 0.8482, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 8423/10000, Train Loss: 1.0359, Train Accuracy: 0.8772, Val Loss: 1.1753, Val Accuracy: 0.7411
Epoch 8424/10000, Train Loss: 1.0441, Train Accuracy: 0.8739, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 8425/10000, Train Loss: 1.0504, Train Accuracy: 0.8627, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 8426/10000, Train Loss: 1.0452, Train Accuracy: 0.8694, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 8427/10000, Train Loss: 1.0563, Train Accuracy: 0.8571, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 8428/10000, Train Loss: 1.0455, Train Accuracy: 0.8672, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 8429/10000, Train Loss: 1.0634, Train Accuracy: 0.8482, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8430/10000, Train Loss: 1.0624, Train Accuracy: 0.8482, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8431/10000, Train Loss: 1.0417, Train Accuracy: 0.8772, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8432/10000, Train Loss: 1.0540, Train Accuracy: 0.8594, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8433/10000, Train Loss: 1.0467, Train Accuracy: 0.8650, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8434/10000, Train Loss: 1.0509, Train Accuracy: 0.8594, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 8435/10000, Train Loss: 1.0573, Train Accuracy: 0.8538, Val Loss: 1.1751, Val Accuracy: 0.7411
Epoch 8436/10000, Train Loss: 1.0510, Train Accuracy: 0.8672, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 8437/10000, Train Loss: 1.0504, Train Accuracy: 0.8638, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 8438/10000, Train Loss: 1.0471, Train Accuracy: 0.8672, Val Loss: 1.1751, Val Accuracy: 0.7411
Epoch 8439/10000, Train Loss: 1.0553, Train Accuracy: 0.8616, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 8440/10000, Train Loss: 1.0452, Train Accuracy: 0.8650, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 8441/10000, Train Loss: 1.0532, Train Accuracy: 0.8504, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 8442/10000, Train Loss: 1.0390, Train Accuracy: 0.8783, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8443/10000, Train Loss: 1.0543, Train Accuracy: 0.8571, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8444/10000, Train Loss: 1.0561, Train Accuracy: 0.8471, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8445/10000, Train Loss: 1.0535, Train Accuracy: 0.8549, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8446/10000, Train Loss: 1.0536, Train Accuracy: 0.8583, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8447/10000, Train Loss: 1.0466, Train Accuracy: 0.8638, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8448/10000, Train Loss: 1.0593, Train Accuracy: 0.8538, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8449/10000, Train Loss: 1.0520, Train Accuracy: 0.8627, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8450/10000, Train Loss: 1.0631, Train Accuracy: 0.8493, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8451/10000, Train Loss: 1.0574, Train Accuracy: 0.8549, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8452/10000, Train Loss: 1.0405, Train Accuracy: 0.8739, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8453/10000, Train Loss: 1.0446, Train Accuracy: 0.8694, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8454/10000, Train Loss: 1.0376, Train Accuracy: 0.8806, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8455/10000, Train Loss: 1.0524, Train Accuracy: 0.8616, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8456/10000, Train Loss: 1.0412, Train Accuracy: 0.8717, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8457/10000, Train Loss: 1.0497, Train Accuracy: 0.8650, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8458/10000, Train Loss: 1.0538, Train Accuracy: 0.8594, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8459/10000, Train Loss: 1.0483, Train Accuracy: 0.8638, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8460/10000, Train Loss: 1.0498, Train Accuracy: 0.8594, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8461/10000, Train Loss: 1.0438, Train Accuracy: 0.8694, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8462/10000, Train Loss: 1.0538, Train Accuracy: 0.8549, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8463/10000, Train Loss: 1.0588, Train Accuracy: 0.8438, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8464/10000, Train Loss: 1.0539, Train Accuracy: 0.8616, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8465/10000, Train Loss: 1.0463, Train Accuracy: 0.8638, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8466/10000, Train Loss: 1.0579, Train Accuracy: 0.8527, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8467/10000, Train Loss: 1.0567, Train Accuracy: 0.8516, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8468/10000, Train Loss: 1.0557, Train Accuracy: 0.8538, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8469/10000, Train Loss: 1.0609, Train Accuracy: 0.8504, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8470/10000, Train Loss: 1.0444, Train Accuracy: 0.8694, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8471/10000, Train Loss: 1.0531, Train Accuracy: 0.8594, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8472/10000, Train Loss: 1.0591, Train Accuracy: 0.8504, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8473/10000, Train Loss: 1.0560, Train Accuracy: 0.8549, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8474/10000, Train Loss: 1.0477, Train Accuracy: 0.8650, Val Loss: 1.1769, Val Accuracy: 0.7411
Epoch 8475/10000, Train Loss: 1.0480, Train Accuracy: 0.8605, Val Loss: 1.1773, Val Accuracy: 0.7366
Epoch 8476/10000, Train Loss: 1.0611, Train Accuracy: 0.8426, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8477/10000, Train Loss: 1.0428, Train Accuracy: 0.8661, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8478/10000, Train Loss: 1.0434, Train Accuracy: 0.8616, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8479/10000, Train Loss: 1.0638, Train Accuracy: 0.8449, Val Loss: 1.1774, Val Accuracy: 0.7366
Epoch 8480/10000, Train Loss: 1.0463, Train Accuracy: 0.8616, Val Loss: 1.1772, Val Accuracy: 0.7366
Epoch 8481/10000, Train Loss: 1.0599, Train Accuracy: 0.8549, Val Loss: 1.1771, Val Accuracy: 0.7366
Epoch 8482/10000, Train Loss: 1.0503, Train Accuracy: 0.8594, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8483/10000, Train Loss: 1.0438, Train Accuracy: 0.8683, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8484/10000, Train Loss: 1.0570, Train Accuracy: 0.8594, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8485/10000, Train Loss: 1.0522, Train Accuracy: 0.8605, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8486/10000, Train Loss: 1.0613, Train Accuracy: 0.8471, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8487/10000, Train Loss: 1.0432, Train Accuracy: 0.8683, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8488/10000, Train Loss: 1.0510, Train Accuracy: 0.8538, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8489/10000, Train Loss: 1.0503, Train Accuracy: 0.8616, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8490/10000, Train Loss: 1.0609, Train Accuracy: 0.8504, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8491/10000, Train Loss: 1.0542, Train Accuracy: 0.8583, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8492/10000, Train Loss: 1.0642, Train Accuracy: 0.8560, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8493/10000, Train Loss: 1.0525, Train Accuracy: 0.8661, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8494/10000, Train Loss: 1.0580, Train Accuracy: 0.8605, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8495/10000, Train Loss: 1.0487, Train Accuracy: 0.8650, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8496/10000, Train Loss: 1.0517, Train Accuracy: 0.8616, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8497/10000, Train Loss: 1.0478, Train Accuracy: 0.8683, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8498/10000, Train Loss: 1.0465, Train Accuracy: 0.8627, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8499/10000, Train Loss: 1.0587, Train Accuracy: 0.8482, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8500/10000, Train Loss: 1.0518, Train Accuracy: 0.8560, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8501/10000, Train Loss: 1.0633, Train Accuracy: 0.8438, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8502/10000, Train Loss: 1.0495, Train Accuracy: 0.8661, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8503/10000, Train Loss: 1.0506, Train Accuracy: 0.8516, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8504/10000, Train Loss: 1.0438, Train Accuracy: 0.8683, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8505/10000, Train Loss: 1.0547, Train Accuracy: 0.8583, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8506/10000, Train Loss: 1.0472, Train Accuracy: 0.8627, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8507/10000, Train Loss: 1.0541, Train Accuracy: 0.8627, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8508/10000, Train Loss: 1.0541, Train Accuracy: 0.8516, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8509/10000, Train Loss: 1.0486, Train Accuracy: 0.8705, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8510/10000, Train Loss: 1.0615, Train Accuracy: 0.8504, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8511/10000, Train Loss: 1.0557, Train Accuracy: 0.8504, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8512/10000, Train Loss: 1.0421, Train Accuracy: 0.8705, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8513/10000, Train Loss: 1.0446, Train Accuracy: 0.8694, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8514/10000, Train Loss: 1.0544, Train Accuracy: 0.8538, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8515/10000, Train Loss: 1.0493, Train Accuracy: 0.8694, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8516/10000, Train Loss: 1.0503, Train Accuracy: 0.8650, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8517/10000, Train Loss: 1.0511, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8518/10000, Train Loss: 1.0483, Train Accuracy: 0.8638, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8519/10000, Train Loss: 1.0538, Train Accuracy: 0.8560, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8520/10000, Train Loss: 1.0444, Train Accuracy: 0.8672, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8521/10000, Train Loss: 1.0487, Train Accuracy: 0.8549, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8522/10000, Train Loss: 1.0537, Train Accuracy: 0.8538, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8523/10000, Train Loss: 1.0507, Train Accuracy: 0.8661, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8524/10000, Train Loss: 1.0538, Train Accuracy: 0.8594, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8525/10000, Train Loss: 1.0279, Train Accuracy: 0.8850, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8526/10000, Train Loss: 1.0422, Train Accuracy: 0.8728, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8527/10000, Train Loss: 1.0554, Train Accuracy: 0.8616, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8528/10000, Train Loss: 1.0485, Train Accuracy: 0.8705, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8529/10000, Train Loss: 1.0350, Train Accuracy: 0.8772, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8530/10000, Train Loss: 1.0489, Train Accuracy: 0.8650, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8531/10000, Train Loss: 1.0534, Train Accuracy: 0.8661, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8532/10000, Train Loss: 1.0512, Train Accuracy: 0.8650, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8533/10000, Train Loss: 1.0469, Train Accuracy: 0.8683, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8534/10000, Train Loss: 1.0534, Train Accuracy: 0.8571, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8535/10000, Train Loss: 1.0370, Train Accuracy: 0.8772, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8536/10000, Train Loss: 1.0420, Train Accuracy: 0.8672, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8537/10000, Train Loss: 1.0493, Train Accuracy: 0.8672, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8538/10000, Train Loss: 1.0659, Train Accuracy: 0.8493, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8539/10000, Train Loss: 1.0498, Train Accuracy: 0.8571, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8540/10000, Train Loss: 1.0460, Train Accuracy: 0.8672, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8541/10000, Train Loss: 1.0519, Train Accuracy: 0.8638, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8542/10000, Train Loss: 1.0571, Train Accuracy: 0.8605, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8543/10000, Train Loss: 1.0595, Train Accuracy: 0.8482, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8544/10000, Train Loss: 1.0484, Train Accuracy: 0.8650, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8545/10000, Train Loss: 1.0477, Train Accuracy: 0.8627, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8546/10000, Train Loss: 1.0545, Train Accuracy: 0.8571, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8547/10000, Train Loss: 1.0473, Train Accuracy: 0.8616, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8548/10000, Train Loss: 1.0378, Train Accuracy: 0.8761, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8549/10000, Train Loss: 1.0585, Train Accuracy: 0.8516, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8550/10000, Train Loss: 1.0532, Train Accuracy: 0.8650, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8551/10000, Train Loss: 1.0609, Train Accuracy: 0.8426, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8552/10000, Train Loss: 1.0694, Train Accuracy: 0.8348, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8553/10000, Train Loss: 1.0420, Train Accuracy: 0.8761, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8554/10000, Train Loss: 1.0499, Train Accuracy: 0.8594, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8555/10000, Train Loss: 1.0465, Train Accuracy: 0.8616, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8556/10000, Train Loss: 1.0423, Train Accuracy: 0.8761, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8557/10000, Train Loss: 1.0494, Train Accuracy: 0.8616, Val Loss: 1.1774, Val Accuracy: 0.7321
Epoch 8558/10000, Train Loss: 1.0614, Train Accuracy: 0.8516, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8559/10000, Train Loss: 1.0512, Train Accuracy: 0.8638, Val Loss: 1.1776, Val Accuracy: 0.7321
Epoch 8560/10000, Train Loss: 1.0426, Train Accuracy: 0.8739, Val Loss: 1.1777, Val Accuracy: 0.7277
Epoch 8561/10000, Train Loss: 1.0572, Train Accuracy: 0.8549, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8562/10000, Train Loss: 1.0486, Train Accuracy: 0.8683, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8563/10000, Train Loss: 1.0501, Train Accuracy: 0.8605, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8564/10000, Train Loss: 1.0555, Train Accuracy: 0.8594, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8565/10000, Train Loss: 1.0540, Train Accuracy: 0.8504, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8566/10000, Train Loss: 1.0369, Train Accuracy: 0.8728, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8567/10000, Train Loss: 1.0542, Train Accuracy: 0.8560, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8568/10000, Train Loss: 1.0465, Train Accuracy: 0.8638, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8569/10000, Train Loss: 1.0532, Train Accuracy: 0.8583, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8570/10000, Train Loss: 1.0512, Train Accuracy: 0.8672, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8571/10000, Train Loss: 1.0459, Train Accuracy: 0.8672, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8572/10000, Train Loss: 1.0594, Train Accuracy: 0.8493, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8573/10000, Train Loss: 1.0497, Train Accuracy: 0.8605, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8574/10000, Train Loss: 1.0499, Train Accuracy: 0.8571, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8575/10000, Train Loss: 1.0396, Train Accuracy: 0.8761, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8576/10000, Train Loss: 1.0513, Train Accuracy: 0.8594, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8577/10000, Train Loss: 1.0460, Train Accuracy: 0.8571, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8578/10000, Train Loss: 1.0461, Train Accuracy: 0.8616, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8579/10000, Train Loss: 1.0532, Train Accuracy: 0.8583, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8580/10000, Train Loss: 1.0394, Train Accuracy: 0.8705, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8581/10000, Train Loss: 1.0447, Train Accuracy: 0.8705, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8582/10000, Train Loss: 1.0465, Train Accuracy: 0.8717, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8583/10000, Train Loss: 1.0479, Train Accuracy: 0.8605, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8584/10000, Train Loss: 1.0482, Train Accuracy: 0.8594, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8585/10000, Train Loss: 1.0501, Train Accuracy: 0.8571, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8586/10000, Train Loss: 1.0449, Train Accuracy: 0.8683, Val Loss: 1.1774, Val Accuracy: 0.7321
Epoch 8587/10000, Train Loss: 1.0499, Train Accuracy: 0.8728, Val Loss: 1.1774, Val Accuracy: 0.7321
Epoch 8588/10000, Train Loss: 1.0454, Train Accuracy: 0.8728, Val Loss: 1.1777, Val Accuracy: 0.7321
Epoch 8589/10000, Train Loss: 1.0454, Train Accuracy: 0.8672, Val Loss: 1.1780, Val Accuracy: 0.7277
Epoch 8590/10000, Train Loss: 1.0439, Train Accuracy: 0.8694, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8591/10000, Train Loss: 1.0486, Train Accuracy: 0.8650, Val Loss: 1.1776, Val Accuracy: 0.7277
Epoch 8592/10000, Train Loss: 1.0441, Train Accuracy: 0.8717, Val Loss: 1.1777, Val Accuracy: 0.7321
Epoch 8593/10000, Train Loss: 1.0470, Train Accuracy: 0.8627, Val Loss: 1.1776, Val Accuracy: 0.7321
Epoch 8594/10000, Train Loss: 1.0339, Train Accuracy: 0.8873, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 8595/10000, Train Loss: 1.0531, Train Accuracy: 0.8638, Val Loss: 1.1777, Val Accuracy: 0.7277
Epoch 8596/10000, Train Loss: 1.0573, Train Accuracy: 0.8527, Val Loss: 1.1776, Val Accuracy: 0.7321
Epoch 8597/10000, Train Loss: 1.0480, Train Accuracy: 0.8638, Val Loss: 1.1777, Val Accuracy: 0.7366
Epoch 8598/10000, Train Loss: 1.0386, Train Accuracy: 0.8761, Val Loss: 1.1778, Val Accuracy: 0.7321
Epoch 8599/10000, Train Loss: 1.0619, Train Accuracy: 0.8404, Val Loss: 1.1778, Val Accuracy: 0.7321
Epoch 8600/10000, Train Loss: 1.0474, Train Accuracy: 0.8672, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8601/10000, Train Loss: 1.0432, Train Accuracy: 0.8705, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8602/10000, Train Loss: 1.0435, Train Accuracy: 0.8683, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8603/10000, Train Loss: 1.0475, Train Accuracy: 0.8694, Val Loss: 1.1780, Val Accuracy: 0.7232
Epoch 8604/10000, Train Loss: 1.0421, Train Accuracy: 0.8694, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8605/10000, Train Loss: 1.0637, Train Accuracy: 0.8382, Val Loss: 1.1779, Val Accuracy: 0.7232
Epoch 8606/10000, Train Loss: 1.0478, Train Accuracy: 0.8627, Val Loss: 1.1780, Val Accuracy: 0.7232
Epoch 8607/10000, Train Loss: 1.0424, Train Accuracy: 0.8694, Val Loss: 1.1779, Val Accuracy: 0.7277
Epoch 8608/10000, Train Loss: 1.0549, Train Accuracy: 0.8549, Val Loss: 1.1777, Val Accuracy: 0.7321
Epoch 8609/10000, Train Loss: 1.0605, Train Accuracy: 0.8449, Val Loss: 1.1778, Val Accuracy: 0.7321
Epoch 8610/10000, Train Loss: 1.0316, Train Accuracy: 0.8783, Val Loss: 1.1779, Val Accuracy: 0.7277
Epoch 8611/10000, Train Loss: 1.0483, Train Accuracy: 0.8638, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8612/10000, Train Loss: 1.0457, Train Accuracy: 0.8672, Val Loss: 1.1776, Val Accuracy: 0.7366
Epoch 8613/10000, Train Loss: 1.0464, Train Accuracy: 0.8694, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8614/10000, Train Loss: 1.0443, Train Accuracy: 0.8683, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8615/10000, Train Loss: 1.0538, Train Accuracy: 0.8594, Val Loss: 1.1778, Val Accuracy: 0.7277
Epoch 8616/10000, Train Loss: 1.0608, Train Accuracy: 0.8449, Val Loss: 1.1776, Val Accuracy: 0.7277
Epoch 8617/10000, Train Loss: 1.0426, Train Accuracy: 0.8705, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8618/10000, Train Loss: 1.0494, Train Accuracy: 0.8650, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8619/10000, Train Loss: 1.0474, Train Accuracy: 0.8661, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8620/10000, Train Loss: 1.0349, Train Accuracy: 0.8783, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8621/10000, Train Loss: 1.0422, Train Accuracy: 0.8705, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8622/10000, Train Loss: 1.0404, Train Accuracy: 0.8672, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8623/10000, Train Loss: 1.0423, Train Accuracy: 0.8728, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8624/10000, Train Loss: 1.0334, Train Accuracy: 0.8884, Val Loss: 1.1769, Val Accuracy: 0.7366
Epoch 8625/10000, Train Loss: 1.0562, Train Accuracy: 0.8549, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8626/10000, Train Loss: 1.0470, Train Accuracy: 0.8694, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8627/10000, Train Loss: 1.0541, Train Accuracy: 0.8504, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8628/10000, Train Loss: 1.0480, Train Accuracy: 0.8683, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8629/10000, Train Loss: 1.0489, Train Accuracy: 0.8549, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8630/10000, Train Loss: 1.0491, Train Accuracy: 0.8627, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8631/10000, Train Loss: 1.0534, Train Accuracy: 0.8605, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8632/10000, Train Loss: 1.0392, Train Accuracy: 0.8761, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8633/10000, Train Loss: 1.0516, Train Accuracy: 0.8571, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8634/10000, Train Loss: 1.0502, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8635/10000, Train Loss: 1.0448, Train Accuracy: 0.8650, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8636/10000, Train Loss: 1.0409, Train Accuracy: 0.8717, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 8637/10000, Train Loss: 1.0486, Train Accuracy: 0.8583, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8638/10000, Train Loss: 1.0465, Train Accuracy: 0.8694, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8639/10000, Train Loss: 1.0590, Train Accuracy: 0.8482, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8640/10000, Train Loss: 1.0497, Train Accuracy: 0.8594, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8641/10000, Train Loss: 1.0614, Train Accuracy: 0.8538, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 8642/10000, Train Loss: 1.0507, Train Accuracy: 0.8583, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 8643/10000, Train Loss: 1.0456, Train Accuracy: 0.8705, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 8644/10000, Train Loss: 1.0397, Train Accuracy: 0.8739, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8645/10000, Train Loss: 1.0436, Train Accuracy: 0.8661, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 8646/10000, Train Loss: 1.0419, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8647/10000, Train Loss: 1.0499, Train Accuracy: 0.8571, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 8648/10000, Train Loss: 1.0567, Train Accuracy: 0.8560, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 8649/10000, Train Loss: 1.0473, Train Accuracy: 0.8672, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8650/10000, Train Loss: 1.0525, Train Accuracy: 0.8571, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8651/10000, Train Loss: 1.0431, Train Accuracy: 0.8650, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 8652/10000, Train Loss: 1.0488, Train Accuracy: 0.8605, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8653/10000, Train Loss: 1.0564, Train Accuracy: 0.8549, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8654/10000, Train Loss: 1.0477, Train Accuracy: 0.8672, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8655/10000, Train Loss: 1.0443, Train Accuracy: 0.8661, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8656/10000, Train Loss: 1.0474, Train Accuracy: 0.8627, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 8657/10000, Train Loss: 1.0420, Train Accuracy: 0.8694, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8658/10000, Train Loss: 1.0398, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8659/10000, Train Loss: 1.0365, Train Accuracy: 0.8795, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8660/10000, Train Loss: 1.0397, Train Accuracy: 0.8739, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 8661/10000, Train Loss: 1.0515, Train Accuracy: 0.8605, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8662/10000, Train Loss: 1.0331, Train Accuracy: 0.8772, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8663/10000, Train Loss: 1.0506, Train Accuracy: 0.8638, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 8664/10000, Train Loss: 1.0436, Train Accuracy: 0.8661, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8665/10000, Train Loss: 1.0428, Train Accuracy: 0.8728, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8666/10000, Train Loss: 1.0490, Train Accuracy: 0.8616, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 8667/10000, Train Loss: 1.0463, Train Accuracy: 0.8661, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 8668/10000, Train Loss: 1.0448, Train Accuracy: 0.8672, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 8669/10000, Train Loss: 1.0507, Train Accuracy: 0.8605, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 8670/10000, Train Loss: 1.0508, Train Accuracy: 0.8616, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 8671/10000, Train Loss: 1.0330, Train Accuracy: 0.8761, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 8672/10000, Train Loss: 1.0505, Train Accuracy: 0.8616, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8673/10000, Train Loss: 1.0468, Train Accuracy: 0.8650, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8674/10000, Train Loss: 1.0361, Train Accuracy: 0.8806, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8675/10000, Train Loss: 1.0482, Train Accuracy: 0.8650, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8676/10000, Train Loss: 1.0610, Train Accuracy: 0.8504, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8677/10000, Train Loss: 1.0435, Train Accuracy: 0.8672, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8678/10000, Train Loss: 1.0453, Train Accuracy: 0.8627, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8679/10000, Train Loss: 1.0395, Train Accuracy: 0.8772, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 8680/10000, Train Loss: 1.0425, Train Accuracy: 0.8739, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 8681/10000, Train Loss: 1.0465, Train Accuracy: 0.8638, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8682/10000, Train Loss: 1.0470, Train Accuracy: 0.8627, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8683/10000, Train Loss: 1.0532, Train Accuracy: 0.8493, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8684/10000, Train Loss: 1.0478, Train Accuracy: 0.8583, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8685/10000, Train Loss: 1.0516, Train Accuracy: 0.8594, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8686/10000, Train Loss: 1.0456, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8687/10000, Train Loss: 1.0378, Train Accuracy: 0.8761, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8688/10000, Train Loss: 1.0397, Train Accuracy: 0.8717, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8689/10000, Train Loss: 1.0603, Train Accuracy: 0.8493, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8690/10000, Train Loss: 1.0602, Train Accuracy: 0.8538, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8691/10000, Train Loss: 1.0299, Train Accuracy: 0.8873, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8692/10000, Train Loss: 1.0477, Train Accuracy: 0.8616, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8693/10000, Train Loss: 1.0542, Train Accuracy: 0.8616, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8694/10000, Train Loss: 1.0495, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8695/10000, Train Loss: 1.0517, Train Accuracy: 0.8538, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8696/10000, Train Loss: 1.0465, Train Accuracy: 0.8661, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8697/10000, Train Loss: 1.0525, Train Accuracy: 0.8583, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8698/10000, Train Loss: 1.0498, Train Accuracy: 0.8650, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8699/10000, Train Loss: 1.0410, Train Accuracy: 0.8728, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8700/10000, Train Loss: 1.0521, Train Accuracy: 0.8616, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8701/10000, Train Loss: 1.0485, Train Accuracy: 0.8672, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8702/10000, Train Loss: 1.0478, Train Accuracy: 0.8627, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8703/10000, Train Loss: 1.0564, Train Accuracy: 0.8460, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8704/10000, Train Loss: 1.0436, Train Accuracy: 0.8761, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8705/10000, Train Loss: 1.0525, Train Accuracy: 0.8616, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8706/10000, Train Loss: 1.0548, Train Accuracy: 0.8560, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8707/10000, Train Loss: 1.0401, Train Accuracy: 0.8717, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8708/10000, Train Loss: 1.0428, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8709/10000, Train Loss: 1.0399, Train Accuracy: 0.8705, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8710/10000, Train Loss: 1.0492, Train Accuracy: 0.8605, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8711/10000, Train Loss: 1.0355, Train Accuracy: 0.8761, Val Loss: 1.1761, Val Accuracy: 0.7321
Epoch 8712/10000, Train Loss: 1.0479, Train Accuracy: 0.8616, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8713/10000, Train Loss: 1.0367, Train Accuracy: 0.8761, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8714/10000, Train Loss: 1.0575, Train Accuracy: 0.8538, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8715/10000, Train Loss: 1.0495, Train Accuracy: 0.8616, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8716/10000, Train Loss: 1.0494, Train Accuracy: 0.8672, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8717/10000, Train Loss: 1.0485, Train Accuracy: 0.8605, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8718/10000, Train Loss: 1.0547, Train Accuracy: 0.8571, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8719/10000, Train Loss: 1.0397, Train Accuracy: 0.8705, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8720/10000, Train Loss: 1.0434, Train Accuracy: 0.8672, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8721/10000, Train Loss: 1.0510, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8722/10000, Train Loss: 1.0433, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8723/10000, Train Loss: 1.0455, Train Accuracy: 0.8705, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8724/10000, Train Loss: 1.0455, Train Accuracy: 0.8638, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8725/10000, Train Loss: 1.0507, Train Accuracy: 0.8605, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8726/10000, Train Loss: 1.0455, Train Accuracy: 0.8683, Val Loss: 1.1774, Val Accuracy: 0.7321
Epoch 8727/10000, Train Loss: 1.0482, Train Accuracy: 0.8627, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8728/10000, Train Loss: 1.0472, Train Accuracy: 0.8650, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8729/10000, Train Loss: 1.0427, Train Accuracy: 0.8750, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8730/10000, Train Loss: 1.0422, Train Accuracy: 0.8717, Val Loss: 1.1774, Val Accuracy: 0.7321
Epoch 8731/10000, Train Loss: 1.0384, Train Accuracy: 0.8705, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8732/10000, Train Loss: 1.0345, Train Accuracy: 0.8783, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8733/10000, Train Loss: 1.0617, Train Accuracy: 0.8415, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8734/10000, Train Loss: 1.0471, Train Accuracy: 0.8694, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8735/10000, Train Loss: 1.0413, Train Accuracy: 0.8705, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8736/10000, Train Loss: 1.0454, Train Accuracy: 0.8661, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8737/10000, Train Loss: 1.0379, Train Accuracy: 0.8783, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8738/10000, Train Loss: 1.0425, Train Accuracy: 0.8717, Val Loss: 1.1776, Val Accuracy: 0.7321
Epoch 8739/10000, Train Loss: 1.0433, Train Accuracy: 0.8627, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8740/10000, Train Loss: 1.0392, Train Accuracy: 0.8739, Val Loss: 1.1775, Val Accuracy: 0.7321
Epoch 8741/10000, Train Loss: 1.0414, Train Accuracy: 0.8705, Val Loss: 1.1773, Val Accuracy: 0.7321
Epoch 8742/10000, Train Loss: 1.0425, Train Accuracy: 0.8750, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8743/10000, Train Loss: 1.0492, Train Accuracy: 0.8605, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8744/10000, Train Loss: 1.0372, Train Accuracy: 0.8772, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8745/10000, Train Loss: 1.0397, Train Accuracy: 0.8728, Val Loss: 1.1772, Val Accuracy: 0.7321
Epoch 8746/10000, Train Loss: 1.0430, Train Accuracy: 0.8705, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8747/10000, Train Loss: 1.0363, Train Accuracy: 0.8750, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8748/10000, Train Loss: 1.0474, Train Accuracy: 0.8616, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8749/10000, Train Loss: 1.0357, Train Accuracy: 0.8761, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8750/10000, Train Loss: 1.0417, Train Accuracy: 0.8750, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8751/10000, Train Loss: 1.0437, Train Accuracy: 0.8728, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8752/10000, Train Loss: 1.0345, Train Accuracy: 0.8783, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8753/10000, Train Loss: 1.0600, Train Accuracy: 0.8460, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8754/10000, Train Loss: 1.0451, Train Accuracy: 0.8705, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8755/10000, Train Loss: 1.0488, Train Accuracy: 0.8571, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8756/10000, Train Loss: 1.0518, Train Accuracy: 0.8549, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8757/10000, Train Loss: 1.0363, Train Accuracy: 0.8761, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8758/10000, Train Loss: 1.0414, Train Accuracy: 0.8717, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8759/10000, Train Loss: 1.0388, Train Accuracy: 0.8694, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8760/10000, Train Loss: 1.0458, Train Accuracy: 0.8683, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8761/10000, Train Loss: 1.0526, Train Accuracy: 0.8616, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8762/10000, Train Loss: 1.0441, Train Accuracy: 0.8650, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8763/10000, Train Loss: 1.0336, Train Accuracy: 0.8806, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8764/10000, Train Loss: 1.0442, Train Accuracy: 0.8661, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8765/10000, Train Loss: 1.0640, Train Accuracy: 0.8504, Val Loss: 1.1770, Val Accuracy: 0.7366
Epoch 8766/10000, Train Loss: 1.0472, Train Accuracy: 0.8650, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8767/10000, Train Loss: 1.0514, Train Accuracy: 0.8605, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8768/10000, Train Loss: 1.0506, Train Accuracy: 0.8672, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8769/10000, Train Loss: 1.0453, Train Accuracy: 0.8683, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8770/10000, Train Loss: 1.0366, Train Accuracy: 0.8705, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8771/10000, Train Loss: 1.0368, Train Accuracy: 0.8728, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8772/10000, Train Loss: 1.0402, Train Accuracy: 0.8761, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8773/10000, Train Loss: 1.0501, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8774/10000, Train Loss: 1.0352, Train Accuracy: 0.8828, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8775/10000, Train Loss: 1.0445, Train Accuracy: 0.8638, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8776/10000, Train Loss: 1.0498, Train Accuracy: 0.8638, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8777/10000, Train Loss: 1.0451, Train Accuracy: 0.8638, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8778/10000, Train Loss: 1.0590, Train Accuracy: 0.8527, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8779/10000, Train Loss: 1.0413, Train Accuracy: 0.8761, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8780/10000, Train Loss: 1.0439, Train Accuracy: 0.8717, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8781/10000, Train Loss: 1.0425, Train Accuracy: 0.8739, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8782/10000, Train Loss: 1.0429, Train Accuracy: 0.8683, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8783/10000, Train Loss: 1.0325, Train Accuracy: 0.8761, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8784/10000, Train Loss: 1.0503, Train Accuracy: 0.8605, Val Loss: 1.1767, Val Accuracy: 0.7366
Epoch 8785/10000, Train Loss: 1.0347, Train Accuracy: 0.8761, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8786/10000, Train Loss: 1.0386, Train Accuracy: 0.8705, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8787/10000, Train Loss: 1.0481, Train Accuracy: 0.8627, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8788/10000, Train Loss: 1.0296, Train Accuracy: 0.8828, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8789/10000, Train Loss: 1.0519, Train Accuracy: 0.8605, Val Loss: 1.1766, Val Accuracy: 0.7366
Epoch 8790/10000, Train Loss: 1.0418, Train Accuracy: 0.8638, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8791/10000, Train Loss: 1.0490, Train Accuracy: 0.8583, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8792/10000, Train Loss: 1.0375, Train Accuracy: 0.8783, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8793/10000, Train Loss: 1.0443, Train Accuracy: 0.8650, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8794/10000, Train Loss: 1.0511, Train Accuracy: 0.8616, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8795/10000, Train Loss: 1.0383, Train Accuracy: 0.8761, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8796/10000, Train Loss: 1.0498, Train Accuracy: 0.8605, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8797/10000, Train Loss: 1.0485, Train Accuracy: 0.8650, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8798/10000, Train Loss: 1.0515, Train Accuracy: 0.8627, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8799/10000, Train Loss: 1.0544, Train Accuracy: 0.8560, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8800/10000, Train Loss: 1.0489, Train Accuracy: 0.8650, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8801/10000, Train Loss: 1.0530, Train Accuracy: 0.8560, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8802/10000, Train Loss: 1.0380, Train Accuracy: 0.8739, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8803/10000, Train Loss: 1.0396, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8804/10000, Train Loss: 1.0461, Train Accuracy: 0.8672, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8805/10000, Train Loss: 1.0503, Train Accuracy: 0.8638, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8806/10000, Train Loss: 1.0382, Train Accuracy: 0.8806, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8807/10000, Train Loss: 1.0420, Train Accuracy: 0.8772, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8808/10000, Train Loss: 1.0497, Train Accuracy: 0.8594, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8809/10000, Train Loss: 1.0400, Train Accuracy: 0.8739, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8810/10000, Train Loss: 1.0486, Train Accuracy: 0.8717, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8811/10000, Train Loss: 1.0455, Train Accuracy: 0.8672, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8812/10000, Train Loss: 1.0298, Train Accuracy: 0.8850, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8813/10000, Train Loss: 1.0454, Train Accuracy: 0.8694, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8814/10000, Train Loss: 1.0446, Train Accuracy: 0.8683, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8815/10000, Train Loss: 1.0414, Train Accuracy: 0.8683, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8816/10000, Train Loss: 1.0372, Train Accuracy: 0.8806, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8817/10000, Train Loss: 1.0464, Train Accuracy: 0.8661, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8818/10000, Train Loss: 1.0457, Train Accuracy: 0.8672, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8819/10000, Train Loss: 1.0385, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8820/10000, Train Loss: 1.0476, Train Accuracy: 0.8672, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8821/10000, Train Loss: 1.0500, Train Accuracy: 0.8638, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8822/10000, Train Loss: 1.0417, Train Accuracy: 0.8694, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8823/10000, Train Loss: 1.0444, Train Accuracy: 0.8638, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8824/10000, Train Loss: 1.0478, Train Accuracy: 0.8538, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8825/10000, Train Loss: 1.0496, Train Accuracy: 0.8571, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8826/10000, Train Loss: 1.0449, Train Accuracy: 0.8605, Val Loss: 1.1762, Val Accuracy: 0.7366
Epoch 8827/10000, Train Loss: 1.0498, Train Accuracy: 0.8627, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8828/10000, Train Loss: 1.0496, Train Accuracy: 0.8594, Val Loss: 1.1768, Val Accuracy: 0.7366
Epoch 8829/10000, Train Loss: 1.0526, Train Accuracy: 0.8638, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8830/10000, Train Loss: 1.0448, Train Accuracy: 0.8672, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8831/10000, Train Loss: 1.0364, Train Accuracy: 0.8717, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8832/10000, Train Loss: 1.0425, Train Accuracy: 0.8672, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8833/10000, Train Loss: 1.0407, Train Accuracy: 0.8750, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8834/10000, Train Loss: 1.0459, Train Accuracy: 0.8638, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8835/10000, Train Loss: 1.0387, Train Accuracy: 0.8672, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8836/10000, Train Loss: 1.0383, Train Accuracy: 0.8761, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8837/10000, Train Loss: 1.0460, Train Accuracy: 0.8627, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8838/10000, Train Loss: 1.0560, Train Accuracy: 0.8527, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8839/10000, Train Loss: 1.0457, Train Accuracy: 0.8661, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8840/10000, Train Loss: 1.0343, Train Accuracy: 0.8828, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8841/10000, Train Loss: 1.0486, Train Accuracy: 0.8661, Val Loss: 1.1769, Val Accuracy: 0.7321
Epoch 8842/10000, Train Loss: 1.0397, Train Accuracy: 0.8705, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8843/10000, Train Loss: 1.0456, Train Accuracy: 0.8627, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8844/10000, Train Loss: 1.0438, Train Accuracy: 0.8638, Val Loss: 1.1771, Val Accuracy: 0.7277
Epoch 8845/10000, Train Loss: 1.0286, Train Accuracy: 0.8817, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8846/10000, Train Loss: 1.0442, Train Accuracy: 0.8627, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8847/10000, Train Loss: 1.0376, Train Accuracy: 0.8772, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8848/10000, Train Loss: 1.0492, Train Accuracy: 0.8583, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8849/10000, Train Loss: 1.0508, Train Accuracy: 0.8594, Val Loss: 1.1771, Val Accuracy: 0.7277
Epoch 8850/10000, Train Loss: 1.0522, Train Accuracy: 0.8583, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 8851/10000, Train Loss: 1.0480, Train Accuracy: 0.8594, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 8852/10000, Train Loss: 1.0420, Train Accuracy: 0.8672, Val Loss: 1.1770, Val Accuracy: 0.7277
Epoch 8853/10000, Train Loss: 1.0471, Train Accuracy: 0.8672, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 8854/10000, Train Loss: 1.0542, Train Accuracy: 0.8527, Val Loss: 1.1771, Val Accuracy: 0.7277
Epoch 8855/10000, Train Loss: 1.0422, Train Accuracy: 0.8661, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8856/10000, Train Loss: 1.0483, Train Accuracy: 0.8650, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8857/10000, Train Loss: 1.0462, Train Accuracy: 0.8605, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8858/10000, Train Loss: 1.0435, Train Accuracy: 0.8650, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8859/10000, Train Loss: 1.0464, Train Accuracy: 0.8683, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8860/10000, Train Loss: 1.0369, Train Accuracy: 0.8750, Val Loss: 1.1777, Val Accuracy: 0.7277
Epoch 8861/10000, Train Loss: 1.0397, Train Accuracy: 0.8728, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8862/10000, Train Loss: 1.0343, Train Accuracy: 0.8772, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8863/10000, Train Loss: 1.0445, Train Accuracy: 0.8694, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8864/10000, Train Loss: 1.0500, Train Accuracy: 0.8616, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8865/10000, Train Loss: 1.0505, Train Accuracy: 0.8527, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 8866/10000, Train Loss: 1.0315, Train Accuracy: 0.8817, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8867/10000, Train Loss: 1.0500, Train Accuracy: 0.8605, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8868/10000, Train Loss: 1.0348, Train Accuracy: 0.8739, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 8869/10000, Train Loss: 1.0395, Train Accuracy: 0.8705, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 8870/10000, Train Loss: 1.0436, Train Accuracy: 0.8683, Val Loss: 1.1777, Val Accuracy: 0.7277
Epoch 8871/10000, Train Loss: 1.0437, Train Accuracy: 0.8694, Val Loss: 1.1776, Val Accuracy: 0.7277
Epoch 8872/10000, Train Loss: 1.0440, Train Accuracy: 0.8683, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8873/10000, Train Loss: 1.0396, Train Accuracy: 0.8694, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8874/10000, Train Loss: 1.0502, Train Accuracy: 0.8594, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8875/10000, Train Loss: 1.0445, Train Accuracy: 0.8638, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8876/10000, Train Loss: 1.0503, Train Accuracy: 0.8594, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8877/10000, Train Loss: 1.0365, Train Accuracy: 0.8739, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8878/10000, Train Loss: 1.0377, Train Accuracy: 0.8795, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8879/10000, Train Loss: 1.0354, Train Accuracy: 0.8795, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8880/10000, Train Loss: 1.0414, Train Accuracy: 0.8739, Val Loss: 1.1771, Val Accuracy: 0.7277
Epoch 8881/10000, Train Loss: 1.0418, Train Accuracy: 0.8717, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 8882/10000, Train Loss: 1.0582, Train Accuracy: 0.8571, Val Loss: 1.1770, Val Accuracy: 0.7277
Epoch 8883/10000, Train Loss: 1.0428, Train Accuracy: 0.8739, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8884/10000, Train Loss: 1.0423, Train Accuracy: 0.8717, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8885/10000, Train Loss: 1.0509, Train Accuracy: 0.8583, Val Loss: 1.1767, Val Accuracy: 0.7321
Epoch 8886/10000, Train Loss: 1.0474, Train Accuracy: 0.8650, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 8887/10000, Train Loss: 1.0256, Train Accuracy: 0.8817, Val Loss: 1.1768, Val Accuracy: 0.7277
Epoch 8888/10000, Train Loss: 1.0386, Train Accuracy: 0.8694, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8889/10000, Train Loss: 1.0410, Train Accuracy: 0.8683, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8890/10000, Train Loss: 1.0396, Train Accuracy: 0.8739, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8891/10000, Train Loss: 1.0445, Train Accuracy: 0.8638, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8892/10000, Train Loss: 1.0547, Train Accuracy: 0.8616, Val Loss: 1.1771, Val Accuracy: 0.7321
Epoch 8893/10000, Train Loss: 1.0357, Train Accuracy: 0.8806, Val Loss: 1.1770, Val Accuracy: 0.7321
Epoch 8894/10000, Train Loss: 1.0435, Train Accuracy: 0.8638, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8895/10000, Train Loss: 1.0409, Train Accuracy: 0.8694, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8896/10000, Train Loss: 1.0497, Train Accuracy: 0.8616, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8897/10000, Train Loss: 1.0550, Train Accuracy: 0.8571, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 8898/10000, Train Loss: 1.0430, Train Accuracy: 0.8705, Val Loss: 1.1773, Val Accuracy: 0.7277
Epoch 8899/10000, Train Loss: 1.0429, Train Accuracy: 0.8750, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 8900/10000, Train Loss: 1.0515, Train Accuracy: 0.8683, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 8901/10000, Train Loss: 1.0388, Train Accuracy: 0.8717, Val Loss: 1.1770, Val Accuracy: 0.7277
Epoch 8902/10000, Train Loss: 1.0421, Train Accuracy: 0.8705, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 8903/10000, Train Loss: 1.0531, Train Accuracy: 0.8527, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 8904/10000, Train Loss: 1.0355, Train Accuracy: 0.8806, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 8905/10000, Train Loss: 1.0242, Train Accuracy: 0.8917, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8906/10000, Train Loss: 1.0395, Train Accuracy: 0.8772, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8907/10000, Train Loss: 1.0419, Train Accuracy: 0.8728, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8908/10000, Train Loss: 1.0407, Train Accuracy: 0.8739, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8909/10000, Train Loss: 1.0376, Train Accuracy: 0.8739, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 8910/10000, Train Loss: 1.0325, Train Accuracy: 0.8817, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 8911/10000, Train Loss: 1.0453, Train Accuracy: 0.8616, Val Loss: 1.1764, Val Accuracy: 0.7277
Epoch 8912/10000, Train Loss: 1.0419, Train Accuracy: 0.8672, Val Loss: 1.1766, Val Accuracy: 0.7277
Epoch 8913/10000, Train Loss: 1.0401, Train Accuracy: 0.8683, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 8914/10000, Train Loss: 1.0541, Train Accuracy: 0.8605, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 8915/10000, Train Loss: 1.0436, Train Accuracy: 0.8661, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8916/10000, Train Loss: 1.0368, Train Accuracy: 0.8739, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 8917/10000, Train Loss: 1.0365, Train Accuracy: 0.8817, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 8918/10000, Train Loss: 1.0428, Train Accuracy: 0.8661, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 8919/10000, Train Loss: 1.0360, Train Accuracy: 0.8795, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 8920/10000, Train Loss: 1.0562, Train Accuracy: 0.8504, Val Loss: 1.1764, Val Accuracy: 0.7321
Epoch 8921/10000, Train Loss: 1.0415, Train Accuracy: 0.8672, Val Loss: 1.1765, Val Accuracy: 0.7366
Epoch 8922/10000, Train Loss: 1.0464, Train Accuracy: 0.8616, Val Loss: 1.1763, Val Accuracy: 0.7411
Epoch 8923/10000, Train Loss: 1.0477, Train Accuracy: 0.8672, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 8924/10000, Train Loss: 1.0499, Train Accuracy: 0.8605, Val Loss: 1.1765, Val Accuracy: 0.7411
Epoch 8925/10000, Train Loss: 1.0500, Train Accuracy: 0.8560, Val Loss: 1.1763, Val Accuracy: 0.7411
Epoch 8926/10000, Train Loss: 1.0344, Train Accuracy: 0.8783, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8927/10000, Train Loss: 1.0462, Train Accuracy: 0.8616, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8928/10000, Train Loss: 1.0462, Train Accuracy: 0.8650, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8929/10000, Train Loss: 1.0463, Train Accuracy: 0.8661, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8930/10000, Train Loss: 1.0493, Train Accuracy: 0.8638, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 8931/10000, Train Loss: 1.0324, Train Accuracy: 0.8806, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 8932/10000, Train Loss: 1.0294, Train Accuracy: 0.8862, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 8933/10000, Train Loss: 1.0488, Train Accuracy: 0.8638, Val Loss: 1.1761, Val Accuracy: 0.7321
Epoch 8934/10000, Train Loss: 1.0404, Train Accuracy: 0.8672, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 8935/10000, Train Loss: 1.0323, Train Accuracy: 0.8806, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8936/10000, Train Loss: 1.0441, Train Accuracy: 0.8650, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 8937/10000, Train Loss: 1.0437, Train Accuracy: 0.8705, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8938/10000, Train Loss: 1.0407, Train Accuracy: 0.8717, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8939/10000, Train Loss: 1.0451, Train Accuracy: 0.8739, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 8940/10000, Train Loss: 1.0480, Train Accuracy: 0.8605, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 8941/10000, Train Loss: 1.0399, Train Accuracy: 0.8717, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8942/10000, Train Loss: 1.0443, Train Accuracy: 0.8717, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8943/10000, Train Loss: 1.0389, Train Accuracy: 0.8705, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8944/10000, Train Loss: 1.0340, Train Accuracy: 0.8862, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8945/10000, Train Loss: 1.0627, Train Accuracy: 0.8471, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8946/10000, Train Loss: 1.0421, Train Accuracy: 0.8683, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8947/10000, Train Loss: 1.0384, Train Accuracy: 0.8717, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8948/10000, Train Loss: 1.0523, Train Accuracy: 0.8605, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8949/10000, Train Loss: 1.0468, Train Accuracy: 0.8650, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8950/10000, Train Loss: 1.0300, Train Accuracy: 0.8839, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8951/10000, Train Loss: 1.0438, Train Accuracy: 0.8717, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8952/10000, Train Loss: 1.0324, Train Accuracy: 0.8806, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8953/10000, Train Loss: 1.0302, Train Accuracy: 0.8873, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 8954/10000, Train Loss: 1.0405, Train Accuracy: 0.8761, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 8955/10000, Train Loss: 1.0405, Train Accuracy: 0.8705, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8956/10000, Train Loss: 1.0357, Train Accuracy: 0.8772, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8957/10000, Train Loss: 1.0471, Train Accuracy: 0.8672, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 8958/10000, Train Loss: 1.0300, Train Accuracy: 0.8884, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 8959/10000, Train Loss: 1.0353, Train Accuracy: 0.8795, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 8960/10000, Train Loss: 1.0363, Train Accuracy: 0.8750, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8961/10000, Train Loss: 1.0347, Train Accuracy: 0.8783, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8962/10000, Train Loss: 1.0443, Train Accuracy: 0.8672, Val Loss: 1.1752, Val Accuracy: 0.7366
Epoch 8963/10000, Train Loss: 1.0441, Train Accuracy: 0.8638, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8964/10000, Train Loss: 1.0459, Train Accuracy: 0.8627, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8965/10000, Train Loss: 1.0374, Train Accuracy: 0.8795, Val Loss: 1.1752, Val Accuracy: 0.7366
Epoch 8966/10000, Train Loss: 1.0376, Train Accuracy: 0.8717, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 8967/10000, Train Loss: 1.0368, Train Accuracy: 0.8795, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 8968/10000, Train Loss: 1.0325, Train Accuracy: 0.8795, Val Loss: 1.1747, Val Accuracy: 0.7411
Epoch 8969/10000, Train Loss: 1.0337, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 8970/10000, Train Loss: 1.0412, Train Accuracy: 0.8739, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 8971/10000, Train Loss: 1.0411, Train Accuracy: 0.8694, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 8972/10000, Train Loss: 1.0331, Train Accuracy: 0.8739, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 8973/10000, Train Loss: 1.0414, Train Accuracy: 0.8683, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8974/10000, Train Loss: 1.0340, Train Accuracy: 0.8761, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 8975/10000, Train Loss: 1.0466, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8976/10000, Train Loss: 1.0432, Train Accuracy: 0.8683, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 8977/10000, Train Loss: 1.0371, Train Accuracy: 0.8728, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8978/10000, Train Loss: 1.0380, Train Accuracy: 0.8728, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8979/10000, Train Loss: 1.0437, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8980/10000, Train Loss: 1.0338, Train Accuracy: 0.8839, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 8981/10000, Train Loss: 1.0363, Train Accuracy: 0.8761, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8982/10000, Train Loss: 1.0406, Train Accuracy: 0.8739, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8983/10000, Train Loss: 1.0511, Train Accuracy: 0.8616, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8984/10000, Train Loss: 1.0434, Train Accuracy: 0.8661, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8985/10000, Train Loss: 1.0387, Train Accuracy: 0.8739, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 8986/10000, Train Loss: 1.0347, Train Accuracy: 0.8795, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8987/10000, Train Loss: 1.0447, Train Accuracy: 0.8705, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 8988/10000, Train Loss: 1.0350, Train Accuracy: 0.8772, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 8989/10000, Train Loss: 1.0368, Train Accuracy: 0.8750, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8990/10000, Train Loss: 1.0279, Train Accuracy: 0.8862, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 8991/10000, Train Loss: 1.0450, Train Accuracy: 0.8694, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 8992/10000, Train Loss: 1.0601, Train Accuracy: 0.8449, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 8993/10000, Train Loss: 1.0569, Train Accuracy: 0.8504, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 8994/10000, Train Loss: 1.0387, Train Accuracy: 0.8705, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 8995/10000, Train Loss: 1.0433, Train Accuracy: 0.8694, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 8996/10000, Train Loss: 1.0395, Train Accuracy: 0.8694, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 8997/10000, Train Loss: 1.0362, Train Accuracy: 0.8761, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 8998/10000, Train Loss: 1.0497, Train Accuracy: 0.8571, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 8999/10000, Train Loss: 1.0364, Train Accuracy: 0.8783, Val Loss: 1.1755, Val Accuracy: 0.7366
Epoch 9000/10000, Train Loss: 1.0457, Train Accuracy: 0.8672, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9001/10000, Train Loss: 1.0307, Train Accuracy: 0.8850, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 9002/10000, Train Loss: 1.0354, Train Accuracy: 0.8806, Val Loss: 1.1761, Val Accuracy: 0.7321
Epoch 9003/10000, Train Loss: 1.0302, Train Accuracy: 0.8850, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9004/10000, Train Loss: 1.0317, Train Accuracy: 0.8795, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9005/10000, Train Loss: 1.0301, Train Accuracy: 0.8895, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9006/10000, Train Loss: 1.0415, Train Accuracy: 0.8694, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9007/10000, Train Loss: 1.0505, Train Accuracy: 0.8549, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9008/10000, Train Loss: 1.0362, Train Accuracy: 0.8772, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9009/10000, Train Loss: 1.0352, Train Accuracy: 0.8806, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9010/10000, Train Loss: 1.0415, Train Accuracy: 0.8661, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9011/10000, Train Loss: 1.0469, Train Accuracy: 0.8627, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9012/10000, Train Loss: 1.0356, Train Accuracy: 0.8772, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9013/10000, Train Loss: 1.0362, Train Accuracy: 0.8772, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9014/10000, Train Loss: 1.0386, Train Accuracy: 0.8728, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 9015/10000, Train Loss: 1.0390, Train Accuracy: 0.8761, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 9016/10000, Train Loss: 1.0366, Train Accuracy: 0.8795, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9017/10000, Train Loss: 1.0302, Train Accuracy: 0.8806, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9018/10000, Train Loss: 1.0343, Train Accuracy: 0.8817, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9019/10000, Train Loss: 1.0515, Train Accuracy: 0.8605, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9020/10000, Train Loss: 1.0431, Train Accuracy: 0.8728, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9021/10000, Train Loss: 1.0421, Train Accuracy: 0.8717, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9022/10000, Train Loss: 1.0367, Train Accuracy: 0.8717, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9023/10000, Train Loss: 1.0396, Train Accuracy: 0.8683, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9024/10000, Train Loss: 1.0456, Train Accuracy: 0.8672, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9025/10000, Train Loss: 1.0360, Train Accuracy: 0.8750, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 9026/10000, Train Loss: 1.0394, Train Accuracy: 0.8694, Val Loss: 1.1761, Val Accuracy: 0.7321
Epoch 9027/10000, Train Loss: 1.0421, Train Accuracy: 0.8650, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9028/10000, Train Loss: 1.0229, Train Accuracy: 0.8929, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9029/10000, Train Loss: 1.0435, Train Accuracy: 0.8672, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9030/10000, Train Loss: 1.0233, Train Accuracy: 0.8906, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9031/10000, Train Loss: 1.0421, Train Accuracy: 0.8694, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 9032/10000, Train Loss: 1.0279, Train Accuracy: 0.8828, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9033/10000, Train Loss: 1.0422, Train Accuracy: 0.8594, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9034/10000, Train Loss: 1.0396, Train Accuracy: 0.8717, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9035/10000, Train Loss: 1.0469, Train Accuracy: 0.8627, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9036/10000, Train Loss: 1.0373, Train Accuracy: 0.8750, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9037/10000, Train Loss: 1.0467, Train Accuracy: 0.8583, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9038/10000, Train Loss: 1.0443, Train Accuracy: 0.8739, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9039/10000, Train Loss: 1.0535, Train Accuracy: 0.8549, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9040/10000, Train Loss: 1.0312, Train Accuracy: 0.8795, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 9041/10000, Train Loss: 1.0447, Train Accuracy: 0.8672, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9042/10000, Train Loss: 1.0439, Train Accuracy: 0.8638, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9043/10000, Train Loss: 1.0506, Train Accuracy: 0.8638, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9044/10000, Train Loss: 1.0406, Train Accuracy: 0.8672, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9045/10000, Train Loss: 1.0261, Train Accuracy: 0.8884, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9046/10000, Train Loss: 1.0430, Train Accuracy: 0.8661, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9047/10000, Train Loss: 1.0384, Train Accuracy: 0.8750, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9048/10000, Train Loss: 1.0456, Train Accuracy: 0.8638, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 9049/10000, Train Loss: 1.0496, Train Accuracy: 0.8616, Val Loss: 1.1761, Val Accuracy: 0.7232
Epoch 9050/10000, Train Loss: 1.0398, Train Accuracy: 0.8683, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 9051/10000, Train Loss: 1.0298, Train Accuracy: 0.8839, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9052/10000, Train Loss: 1.0369, Train Accuracy: 0.8761, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9053/10000, Train Loss: 1.0397, Train Accuracy: 0.8705, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9054/10000, Train Loss: 1.0471, Train Accuracy: 0.8616, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9055/10000, Train Loss: 1.0363, Train Accuracy: 0.8717, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9056/10000, Train Loss: 1.0328, Train Accuracy: 0.8750, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9057/10000, Train Loss: 1.0304, Train Accuracy: 0.8783, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9058/10000, Train Loss: 1.0407, Train Accuracy: 0.8728, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9059/10000, Train Loss: 1.0410, Train Accuracy: 0.8783, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9060/10000, Train Loss: 1.0409, Train Accuracy: 0.8739, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9061/10000, Train Loss: 1.0336, Train Accuracy: 0.8817, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9062/10000, Train Loss: 1.0334, Train Accuracy: 0.8783, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9063/10000, Train Loss: 1.0398, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9064/10000, Train Loss: 1.0423, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9065/10000, Train Loss: 1.0373, Train Accuracy: 0.8728, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9066/10000, Train Loss: 1.0388, Train Accuracy: 0.8761, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9067/10000, Train Loss: 1.0303, Train Accuracy: 0.8873, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9068/10000, Train Loss: 1.0357, Train Accuracy: 0.8728, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9069/10000, Train Loss: 1.0424, Train Accuracy: 0.8739, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9070/10000, Train Loss: 1.0435, Train Accuracy: 0.8683, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9071/10000, Train Loss: 1.0331, Train Accuracy: 0.8761, Val Loss: 1.1739, Val Accuracy: 0.7366
Epoch 9072/10000, Train Loss: 1.0375, Train Accuracy: 0.8739, Val Loss: 1.1738, Val Accuracy: 0.7366
Epoch 9073/10000, Train Loss: 1.0370, Train Accuracy: 0.8728, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9074/10000, Train Loss: 1.0234, Train Accuracy: 0.8862, Val Loss: 1.1742, Val Accuracy: 0.7411
Epoch 9075/10000, Train Loss: 1.0403, Train Accuracy: 0.8661, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9076/10000, Train Loss: 1.0306, Train Accuracy: 0.8806, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9077/10000, Train Loss: 1.0364, Train Accuracy: 0.8750, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9078/10000, Train Loss: 1.0423, Train Accuracy: 0.8683, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9079/10000, Train Loss: 1.0371, Train Accuracy: 0.8739, Val Loss: 1.1747, Val Accuracy: 0.7411
Epoch 9080/10000, Train Loss: 1.0341, Train Accuracy: 0.8772, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9081/10000, Train Loss: 1.0339, Train Accuracy: 0.8705, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9082/10000, Train Loss: 1.0499, Train Accuracy: 0.8605, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9083/10000, Train Loss: 1.0528, Train Accuracy: 0.8594, Val Loss: 1.1740, Val Accuracy: 0.7411
Epoch 9084/10000, Train Loss: 1.0361, Train Accuracy: 0.8817, Val Loss: 1.1737, Val Accuracy: 0.7411
Epoch 9085/10000, Train Loss: 1.0343, Train Accuracy: 0.8772, Val Loss: 1.1736, Val Accuracy: 0.7411
Epoch 9086/10000, Train Loss: 1.0351, Train Accuracy: 0.8772, Val Loss: 1.1738, Val Accuracy: 0.7411
Epoch 9087/10000, Train Loss: 1.0484, Train Accuracy: 0.8650, Val Loss: 1.1740, Val Accuracy: 0.7411
Epoch 9088/10000, Train Loss: 1.0473, Train Accuracy: 0.8616, Val Loss: 1.1740, Val Accuracy: 0.7411
Epoch 9089/10000, Train Loss: 1.0341, Train Accuracy: 0.8783, Val Loss: 1.1739, Val Accuracy: 0.7366
Epoch 9090/10000, Train Loss: 1.0278, Train Accuracy: 0.8839, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9091/10000, Train Loss: 1.0309, Train Accuracy: 0.8806, Val Loss: 1.1742, Val Accuracy: 0.7366
Epoch 9092/10000, Train Loss: 1.0434, Train Accuracy: 0.8638, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9093/10000, Train Loss: 1.0310, Train Accuracy: 0.8862, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9094/10000, Train Loss: 1.0252, Train Accuracy: 0.8873, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9095/10000, Train Loss: 1.0342, Train Accuracy: 0.8839, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9096/10000, Train Loss: 1.0416, Train Accuracy: 0.8739, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9097/10000, Train Loss: 1.0212, Train Accuracy: 0.8973, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9098/10000, Train Loss: 1.0377, Train Accuracy: 0.8705, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9099/10000, Train Loss: 1.0447, Train Accuracy: 0.8616, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9100/10000, Train Loss: 1.0364, Train Accuracy: 0.8705, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9101/10000, Train Loss: 1.0450, Train Accuracy: 0.8627, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9102/10000, Train Loss: 1.0303, Train Accuracy: 0.8873, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9103/10000, Train Loss: 1.0329, Train Accuracy: 0.8828, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9104/10000, Train Loss: 1.0257, Train Accuracy: 0.8929, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9105/10000, Train Loss: 1.0451, Train Accuracy: 0.8705, Val Loss: 1.1752, Val Accuracy: 0.7366
Epoch 9106/10000, Train Loss: 1.0475, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9107/10000, Train Loss: 1.0378, Train Accuracy: 0.8739, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9108/10000, Train Loss: 1.0415, Train Accuracy: 0.8683, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9109/10000, Train Loss: 1.0390, Train Accuracy: 0.8739, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9110/10000, Train Loss: 1.0318, Train Accuracy: 0.8862, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9111/10000, Train Loss: 1.0493, Train Accuracy: 0.8571, Val Loss: 1.1745, Val Accuracy: 0.7411
Epoch 9112/10000, Train Loss: 1.0345, Train Accuracy: 0.8806, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9113/10000, Train Loss: 1.0384, Train Accuracy: 0.8795, Val Loss: 1.1748, Val Accuracy: 0.7411
Epoch 9114/10000, Train Loss: 1.0298, Train Accuracy: 0.8806, Val Loss: 1.1749, Val Accuracy: 0.7411
Epoch 9115/10000, Train Loss: 1.0496, Train Accuracy: 0.8571, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9116/10000, Train Loss: 1.0387, Train Accuracy: 0.8795, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9117/10000, Train Loss: 1.0299, Train Accuracy: 0.8850, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9118/10000, Train Loss: 1.0340, Train Accuracy: 0.8783, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9119/10000, Train Loss: 1.0327, Train Accuracy: 0.8806, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9120/10000, Train Loss: 1.0484, Train Accuracy: 0.8583, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9121/10000, Train Loss: 1.0479, Train Accuracy: 0.8616, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9122/10000, Train Loss: 1.0374, Train Accuracy: 0.8728, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9123/10000, Train Loss: 1.0370, Train Accuracy: 0.8761, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9124/10000, Train Loss: 1.0387, Train Accuracy: 0.8717, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9125/10000, Train Loss: 1.0471, Train Accuracy: 0.8616, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9126/10000, Train Loss: 1.0334, Train Accuracy: 0.8817, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9127/10000, Train Loss: 1.0385, Train Accuracy: 0.8705, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9128/10000, Train Loss: 1.0372, Train Accuracy: 0.8795, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9129/10000, Train Loss: 1.0349, Train Accuracy: 0.8795, Val Loss: 1.1745, Val Accuracy: 0.7411
Epoch 9130/10000, Train Loss: 1.0271, Train Accuracy: 0.8806, Val Loss: 1.1741, Val Accuracy: 0.7411
Epoch 9131/10000, Train Loss: 1.0418, Train Accuracy: 0.8728, Val Loss: 1.1743, Val Accuracy: 0.7411
Epoch 9132/10000, Train Loss: 1.0410, Train Accuracy: 0.8683, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9133/10000, Train Loss: 1.0292, Train Accuracy: 0.8862, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9134/10000, Train Loss: 1.0546, Train Accuracy: 0.8560, Val Loss: 1.1746, Val Accuracy: 0.7411
Epoch 9135/10000, Train Loss: 1.0412, Train Accuracy: 0.8761, Val Loss: 1.1745, Val Accuracy: 0.7411
Epoch 9136/10000, Train Loss: 1.0466, Train Accuracy: 0.8638, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9137/10000, Train Loss: 1.0415, Train Accuracy: 0.8583, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9138/10000, Train Loss: 1.0359, Train Accuracy: 0.8783, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9139/10000, Train Loss: 1.0302, Train Accuracy: 0.8884, Val Loss: 1.1743, Val Accuracy: 0.7411
Epoch 9140/10000, Train Loss: 1.0394, Train Accuracy: 0.8705, Val Loss: 1.1741, Val Accuracy: 0.7411
Epoch 9141/10000, Train Loss: 1.0445, Train Accuracy: 0.8616, Val Loss: 1.1741, Val Accuracy: 0.7411
Epoch 9142/10000, Train Loss: 1.0392, Train Accuracy: 0.8728, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9143/10000, Train Loss: 1.0379, Train Accuracy: 0.8728, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9144/10000, Train Loss: 1.0370, Train Accuracy: 0.8694, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9145/10000, Train Loss: 1.0338, Train Accuracy: 0.8728, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9146/10000, Train Loss: 1.0465, Train Accuracy: 0.8549, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9147/10000, Train Loss: 1.0410, Train Accuracy: 0.8650, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9148/10000, Train Loss: 1.0439, Train Accuracy: 0.8616, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9149/10000, Train Loss: 1.0519, Train Accuracy: 0.8594, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9150/10000, Train Loss: 1.0362, Train Accuracy: 0.8750, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9151/10000, Train Loss: 1.0346, Train Accuracy: 0.8795, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9152/10000, Train Loss: 1.0311, Train Accuracy: 0.8795, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9153/10000, Train Loss: 1.0243, Train Accuracy: 0.8862, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9154/10000, Train Loss: 1.0418, Train Accuracy: 0.8739, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9155/10000, Train Loss: 1.0468, Train Accuracy: 0.8650, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9156/10000, Train Loss: 1.0416, Train Accuracy: 0.8717, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9157/10000, Train Loss: 1.0248, Train Accuracy: 0.8862, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9158/10000, Train Loss: 1.0423, Train Accuracy: 0.8728, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9159/10000, Train Loss: 1.0398, Train Accuracy: 0.8717, Val Loss: 1.1747, Val Accuracy: 0.7411
Epoch 9160/10000, Train Loss: 1.0274, Train Accuracy: 0.8839, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9161/10000, Train Loss: 1.0362, Train Accuracy: 0.8783, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 9162/10000, Train Loss: 1.0342, Train Accuracy: 0.8806, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9163/10000, Train Loss: 1.0330, Train Accuracy: 0.8783, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9164/10000, Train Loss: 1.0241, Train Accuracy: 0.8884, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9165/10000, Train Loss: 1.0211, Train Accuracy: 0.8940, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9166/10000, Train Loss: 1.0385, Train Accuracy: 0.8705, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9167/10000, Train Loss: 1.0354, Train Accuracy: 0.8750, Val Loss: 1.1747, Val Accuracy: 0.7411
Epoch 9168/10000, Train Loss: 1.0418, Train Accuracy: 0.8705, Val Loss: 1.1745, Val Accuracy: 0.7411
Epoch 9169/10000, Train Loss: 1.0334, Train Accuracy: 0.8806, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9170/10000, Train Loss: 1.0387, Train Accuracy: 0.8739, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9171/10000, Train Loss: 1.0325, Train Accuracy: 0.8761, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9172/10000, Train Loss: 1.0366, Train Accuracy: 0.8739, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9173/10000, Train Loss: 1.0395, Train Accuracy: 0.8717, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9174/10000, Train Loss: 1.0269, Train Accuracy: 0.8839, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9175/10000, Train Loss: 1.0356, Train Accuracy: 0.8739, Val Loss: 1.1746, Val Accuracy: 0.7411
Epoch 9176/10000, Train Loss: 1.0363, Train Accuracy: 0.8850, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9177/10000, Train Loss: 1.0353, Train Accuracy: 0.8728, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 9178/10000, Train Loss: 1.0392, Train Accuracy: 0.8806, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9179/10000, Train Loss: 1.0331, Train Accuracy: 0.8739, Val Loss: 1.1742, Val Accuracy: 0.7366
Epoch 9180/10000, Train Loss: 1.0399, Train Accuracy: 0.8683, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9181/10000, Train Loss: 1.0254, Train Accuracy: 0.8862, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9182/10000, Train Loss: 1.0246, Train Accuracy: 0.8873, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9183/10000, Train Loss: 1.0340, Train Accuracy: 0.8750, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9184/10000, Train Loss: 1.0357, Train Accuracy: 0.8795, Val Loss: 1.1744, Val Accuracy: 0.7411
Epoch 9185/10000, Train Loss: 1.0391, Train Accuracy: 0.8683, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9186/10000, Train Loss: 1.0388, Train Accuracy: 0.8683, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9187/10000, Train Loss: 1.0396, Train Accuracy: 0.8728, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9188/10000, Train Loss: 1.0375, Train Accuracy: 0.8739, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9189/10000, Train Loss: 1.0306, Train Accuracy: 0.8761, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9190/10000, Train Loss: 1.0319, Train Accuracy: 0.8772, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9191/10000, Train Loss: 1.0293, Train Accuracy: 0.8862, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9192/10000, Train Loss: 1.0361, Train Accuracy: 0.8717, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9193/10000, Train Loss: 1.0262, Train Accuracy: 0.8873, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 9194/10000, Train Loss: 1.0270, Train Accuracy: 0.8850, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9195/10000, Train Loss: 1.0394, Train Accuracy: 0.8683, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9196/10000, Train Loss: 1.0402, Train Accuracy: 0.8683, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9197/10000, Train Loss: 1.0366, Train Accuracy: 0.8806, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9198/10000, Train Loss: 1.0467, Train Accuracy: 0.8627, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9199/10000, Train Loss: 1.0329, Train Accuracy: 0.8739, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9200/10000, Train Loss: 1.0371, Train Accuracy: 0.8750, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9201/10000, Train Loss: 1.0340, Train Accuracy: 0.8739, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9202/10000, Train Loss: 1.0421, Train Accuracy: 0.8661, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9203/10000, Train Loss: 1.0388, Train Accuracy: 0.8761, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9204/10000, Train Loss: 1.0318, Train Accuracy: 0.8806, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9205/10000, Train Loss: 1.0462, Train Accuracy: 0.8683, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9206/10000, Train Loss: 1.0297, Train Accuracy: 0.8761, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9207/10000, Train Loss: 1.0374, Train Accuracy: 0.8728, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9208/10000, Train Loss: 1.0337, Train Accuracy: 0.8783, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9209/10000, Train Loss: 1.0470, Train Accuracy: 0.8650, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9210/10000, Train Loss: 1.0345, Train Accuracy: 0.8817, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9211/10000, Train Loss: 1.0326, Train Accuracy: 0.8783, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9212/10000, Train Loss: 1.0444, Train Accuracy: 0.8750, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9213/10000, Train Loss: 1.0327, Train Accuracy: 0.8839, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9214/10000, Train Loss: 1.0354, Train Accuracy: 0.8761, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9215/10000, Train Loss: 1.0347, Train Accuracy: 0.8717, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9216/10000, Train Loss: 1.0444, Train Accuracy: 0.8661, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9217/10000, Train Loss: 1.0353, Train Accuracy: 0.8739, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9218/10000, Train Loss: 1.0409, Train Accuracy: 0.8672, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9219/10000, Train Loss: 1.0391, Train Accuracy: 0.8694, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9220/10000, Train Loss: 1.0340, Train Accuracy: 0.8739, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9221/10000, Train Loss: 1.0300, Train Accuracy: 0.8772, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9222/10000, Train Loss: 1.0360, Train Accuracy: 0.8750, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9223/10000, Train Loss: 1.0381, Train Accuracy: 0.8739, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9224/10000, Train Loss: 1.0451, Train Accuracy: 0.8605, Val Loss: 1.1742, Val Accuracy: 0.7366
Epoch 9225/10000, Train Loss: 1.0399, Train Accuracy: 0.8683, Val Loss: 1.1745, Val Accuracy: 0.7366
Epoch 9226/10000, Train Loss: 1.0416, Train Accuracy: 0.8705, Val Loss: 1.1746, Val Accuracy: 0.7366
Epoch 9227/10000, Train Loss: 1.0314, Train Accuracy: 0.8850, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9228/10000, Train Loss: 1.0435, Train Accuracy: 0.8616, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9229/10000, Train Loss: 1.0304, Train Accuracy: 0.8817, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9230/10000, Train Loss: 1.0469, Train Accuracy: 0.8571, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9231/10000, Train Loss: 1.0351, Train Accuracy: 0.8761, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9232/10000, Train Loss: 1.0362, Train Accuracy: 0.8772, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9233/10000, Train Loss: 1.0392, Train Accuracy: 0.8683, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9234/10000, Train Loss: 1.0365, Train Accuracy: 0.8750, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9235/10000, Train Loss: 1.0500, Train Accuracy: 0.8571, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9236/10000, Train Loss: 1.0296, Train Accuracy: 0.8750, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9237/10000, Train Loss: 1.0205, Train Accuracy: 0.8862, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9238/10000, Train Loss: 1.0292, Train Accuracy: 0.8862, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9239/10000, Train Loss: 1.0522, Train Accuracy: 0.8638, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9240/10000, Train Loss: 1.0334, Train Accuracy: 0.8772, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9241/10000, Train Loss: 1.0265, Train Accuracy: 0.8839, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9242/10000, Train Loss: 1.0364, Train Accuracy: 0.8772, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9243/10000, Train Loss: 1.0309, Train Accuracy: 0.8828, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9244/10000, Train Loss: 1.0441, Train Accuracy: 0.8705, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9245/10000, Train Loss: 1.0351, Train Accuracy: 0.8739, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9246/10000, Train Loss: 1.0434, Train Accuracy: 0.8672, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9247/10000, Train Loss: 1.0372, Train Accuracy: 0.8705, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9248/10000, Train Loss: 1.0477, Train Accuracy: 0.8594, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9249/10000, Train Loss: 1.0367, Train Accuracy: 0.8728, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9250/10000, Train Loss: 1.0427, Train Accuracy: 0.8683, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9251/10000, Train Loss: 1.0289, Train Accuracy: 0.8783, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9252/10000, Train Loss: 1.0253, Train Accuracy: 0.8895, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9253/10000, Train Loss: 1.0336, Train Accuracy: 0.8783, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9254/10000, Train Loss: 1.0303, Train Accuracy: 0.8828, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9255/10000, Train Loss: 1.0324, Train Accuracy: 0.8783, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9256/10000, Train Loss: 1.0294, Train Accuracy: 0.8884, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9257/10000, Train Loss: 1.0405, Train Accuracy: 0.8717, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9258/10000, Train Loss: 1.0465, Train Accuracy: 0.8627, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9259/10000, Train Loss: 1.0416, Train Accuracy: 0.8650, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9260/10000, Train Loss: 1.0327, Train Accuracy: 0.8795, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9261/10000, Train Loss: 1.0330, Train Accuracy: 0.8750, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9262/10000, Train Loss: 1.0312, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9263/10000, Train Loss: 1.0322, Train Accuracy: 0.8783, Val Loss: 1.1754, Val Accuracy: 0.7232
Epoch 9264/10000, Train Loss: 1.0197, Train Accuracy: 0.8973, Val Loss: 1.1753, Val Accuracy: 0.7232
Epoch 9265/10000, Train Loss: 1.0410, Train Accuracy: 0.8694, Val Loss: 1.1754, Val Accuracy: 0.7232
Epoch 9266/10000, Train Loss: 1.0236, Train Accuracy: 0.8884, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9267/10000, Train Loss: 1.0280, Train Accuracy: 0.8817, Val Loss: 1.1761, Val Accuracy: 0.7232
Epoch 9268/10000, Train Loss: 1.0362, Train Accuracy: 0.8750, Val Loss: 1.1764, Val Accuracy: 0.7232
Epoch 9269/10000, Train Loss: 1.0279, Train Accuracy: 0.8839, Val Loss: 1.1761, Val Accuracy: 0.7232
Epoch 9270/10000, Train Loss: 1.0305, Train Accuracy: 0.8850, Val Loss: 1.1762, Val Accuracy: 0.7232
Epoch 9271/10000, Train Loss: 1.0313, Train Accuracy: 0.8839, Val Loss: 1.1764, Val Accuracy: 0.7232
Epoch 9272/10000, Train Loss: 1.0281, Train Accuracy: 0.8862, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 9273/10000, Train Loss: 1.0315, Train Accuracy: 0.8850, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 9274/10000, Train Loss: 1.0247, Train Accuracy: 0.8850, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9275/10000, Train Loss: 1.0269, Train Accuracy: 0.8850, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9276/10000, Train Loss: 1.0270, Train Accuracy: 0.8828, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9277/10000, Train Loss: 1.0369, Train Accuracy: 0.8717, Val Loss: 1.1763, Val Accuracy: 0.7232
Epoch 9278/10000, Train Loss: 1.0438, Train Accuracy: 0.8683, Val Loss: 1.1763, Val Accuracy: 0.7232
Epoch 9279/10000, Train Loss: 1.0314, Train Accuracy: 0.8828, Val Loss: 1.1764, Val Accuracy: 0.7232
Epoch 9280/10000, Train Loss: 1.0435, Train Accuracy: 0.8638, Val Loss: 1.1765, Val Accuracy: 0.7232
Epoch 9281/10000, Train Loss: 1.0414, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7232
Epoch 9282/10000, Train Loss: 1.0227, Train Accuracy: 0.8873, Val Loss: 1.1764, Val Accuracy: 0.7232
Epoch 9283/10000, Train Loss: 1.0208, Train Accuracy: 0.8973, Val Loss: 1.1765, Val Accuracy: 0.7232
Epoch 9284/10000, Train Loss: 1.0354, Train Accuracy: 0.8772, Val Loss: 1.1766, Val Accuracy: 0.7232
Epoch 9285/10000, Train Loss: 1.0343, Train Accuracy: 0.8783, Val Loss: 1.1767, Val Accuracy: 0.7232
Epoch 9286/10000, Train Loss: 1.0471, Train Accuracy: 0.8571, Val Loss: 1.1767, Val Accuracy: 0.7232
Epoch 9287/10000, Train Loss: 1.0315, Train Accuracy: 0.8750, Val Loss: 1.1769, Val Accuracy: 0.7232
Epoch 9288/10000, Train Loss: 1.0387, Train Accuracy: 0.8739, Val Loss: 1.1768, Val Accuracy: 0.7232
Epoch 9289/10000, Train Loss: 1.0309, Train Accuracy: 0.8705, Val Loss: 1.1772, Val Accuracy: 0.7232
Epoch 9290/10000, Train Loss: 1.0481, Train Accuracy: 0.8661, Val Loss: 1.1775, Val Accuracy: 0.7232
Epoch 9291/10000, Train Loss: 1.0377, Train Accuracy: 0.8717, Val Loss: 1.1777, Val Accuracy: 0.7232
Epoch 9292/10000, Train Loss: 1.0496, Train Accuracy: 0.8616, Val Loss: 1.1772, Val Accuracy: 0.7232
Epoch 9293/10000, Train Loss: 1.0289, Train Accuracy: 0.8850, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9294/10000, Train Loss: 1.0266, Train Accuracy: 0.8862, Val Loss: 1.1776, Val Accuracy: 0.7232
Epoch 9295/10000, Train Loss: 1.0314, Train Accuracy: 0.8817, Val Loss: 1.1775, Val Accuracy: 0.7232
Epoch 9296/10000, Train Loss: 1.0394, Train Accuracy: 0.8761, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9297/10000, Train Loss: 1.0468, Train Accuracy: 0.8683, Val Loss: 1.1776, Val Accuracy: 0.7232
Epoch 9298/10000, Train Loss: 1.0276, Train Accuracy: 0.8895, Val Loss: 1.1776, Val Accuracy: 0.7232
Epoch 9299/10000, Train Loss: 1.0398, Train Accuracy: 0.8672, Val Loss: 1.1778, Val Accuracy: 0.7232
Epoch 9300/10000, Train Loss: 1.0455, Train Accuracy: 0.8616, Val Loss: 1.1772, Val Accuracy: 0.7232
Epoch 9301/10000, Train Loss: 1.0313, Train Accuracy: 0.8795, Val Loss: 1.1773, Val Accuracy: 0.7232
Epoch 9302/10000, Train Loss: 1.0371, Train Accuracy: 0.8783, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9303/10000, Train Loss: 1.0388, Train Accuracy: 0.8694, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9304/10000, Train Loss: 1.0283, Train Accuracy: 0.8917, Val Loss: 1.1773, Val Accuracy: 0.7232
Epoch 9305/10000, Train Loss: 1.0418, Train Accuracy: 0.8672, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9306/10000, Train Loss: 1.0485, Train Accuracy: 0.8571, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9307/10000, Train Loss: 1.0379, Train Accuracy: 0.8705, Val Loss: 1.1775, Val Accuracy: 0.7232
Epoch 9308/10000, Train Loss: 1.0360, Train Accuracy: 0.8739, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9309/10000, Train Loss: 1.0389, Train Accuracy: 0.8683, Val Loss: 1.1775, Val Accuracy: 0.7232
Epoch 9310/10000, Train Loss: 1.0390, Train Accuracy: 0.8728, Val Loss: 1.1774, Val Accuracy: 0.7232
Epoch 9311/10000, Train Loss: 1.0355, Train Accuracy: 0.8761, Val Loss: 1.1773, Val Accuracy: 0.7232
Epoch 9312/10000, Train Loss: 1.0322, Train Accuracy: 0.8795, Val Loss: 1.1776, Val Accuracy: 0.7232
Epoch 9313/10000, Train Loss: 1.0382, Train Accuracy: 0.8750, Val Loss: 1.1779, Val Accuracy: 0.7277
Epoch 9314/10000, Train Loss: 1.0404, Train Accuracy: 0.8694, Val Loss: 1.1777, Val Accuracy: 0.7277
Epoch 9315/10000, Train Loss: 1.0352, Train Accuracy: 0.8683, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 9316/10000, Train Loss: 1.0236, Train Accuracy: 0.8895, Val Loss: 1.1775, Val Accuracy: 0.7277
Epoch 9317/10000, Train Loss: 1.0402, Train Accuracy: 0.8750, Val Loss: 1.1777, Val Accuracy: 0.7232
Epoch 9318/10000, Train Loss: 1.0378, Train Accuracy: 0.8717, Val Loss: 1.1778, Val Accuracy: 0.7232
Epoch 9319/10000, Train Loss: 1.0293, Train Accuracy: 0.8806, Val Loss: 1.1775, Val Accuracy: 0.7188
Epoch 9320/10000, Train Loss: 1.0305, Train Accuracy: 0.8772, Val Loss: 1.1772, Val Accuracy: 0.7232
Epoch 9321/10000, Train Loss: 1.0449, Train Accuracy: 0.8694, Val Loss: 1.1772, Val Accuracy: 0.7232
Epoch 9322/10000, Train Loss: 1.0301, Train Accuracy: 0.8873, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9323/10000, Train Loss: 1.0456, Train Accuracy: 0.8750, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9324/10000, Train Loss: 1.0395, Train Accuracy: 0.8650, Val Loss: 1.1765, Val Accuracy: 0.7277
Epoch 9325/10000, Train Loss: 1.0324, Train Accuracy: 0.8705, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9326/10000, Train Loss: 1.0293, Train Accuracy: 0.8761, Val Loss: 1.1770, Val Accuracy: 0.7277
Epoch 9327/10000, Train Loss: 1.0281, Train Accuracy: 0.8862, Val Loss: 1.1774, Val Accuracy: 0.7277
Epoch 9328/10000, Train Loss: 1.0389, Train Accuracy: 0.8683, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 9329/10000, Train Loss: 1.0400, Train Accuracy: 0.8705, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 9330/10000, Train Loss: 1.0384, Train Accuracy: 0.8694, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9331/10000, Train Loss: 1.0304, Train Accuracy: 0.8806, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9332/10000, Train Loss: 1.0286, Train Accuracy: 0.8884, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 9333/10000, Train Loss: 1.0406, Train Accuracy: 0.8750, Val Loss: 1.1767, Val Accuracy: 0.7277
Epoch 9334/10000, Train Loss: 1.0298, Train Accuracy: 0.8750, Val Loss: 1.1770, Val Accuracy: 0.7277
Epoch 9335/10000, Train Loss: 1.0401, Train Accuracy: 0.8739, Val Loss: 1.1772, Val Accuracy: 0.7277
Epoch 9336/10000, Train Loss: 1.0300, Train Accuracy: 0.8795, Val Loss: 1.1769, Val Accuracy: 0.7277
Epoch 9337/10000, Train Loss: 1.0310, Train Accuracy: 0.8828, Val Loss: 1.1766, Val Accuracy: 0.7277
Epoch 9338/10000, Train Loss: 1.0434, Train Accuracy: 0.8683, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 9339/10000, Train Loss: 1.0287, Train Accuracy: 0.8828, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9340/10000, Train Loss: 1.0208, Train Accuracy: 0.8940, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9341/10000, Train Loss: 1.0226, Train Accuracy: 0.8917, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9342/10000, Train Loss: 1.0308, Train Accuracy: 0.8839, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9343/10000, Train Loss: 1.0417, Train Accuracy: 0.8705, Val Loss: 1.1756, Val Accuracy: 0.7277
Epoch 9344/10000, Train Loss: 1.0349, Train Accuracy: 0.8739, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9345/10000, Train Loss: 1.0260, Train Accuracy: 0.8839, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9346/10000, Train Loss: 1.0286, Train Accuracy: 0.8817, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9347/10000, Train Loss: 1.0248, Train Accuracy: 0.8951, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9348/10000, Train Loss: 1.0345, Train Accuracy: 0.8717, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9349/10000, Train Loss: 1.0384, Train Accuracy: 0.8761, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9350/10000, Train Loss: 1.0377, Train Accuracy: 0.8761, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9351/10000, Train Loss: 1.0432, Train Accuracy: 0.8717, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9352/10000, Train Loss: 1.0278, Train Accuracy: 0.8884, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9353/10000, Train Loss: 1.0377, Train Accuracy: 0.8705, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9354/10000, Train Loss: 1.0257, Train Accuracy: 0.8929, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9355/10000, Train Loss: 1.0443, Train Accuracy: 0.8661, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9356/10000, Train Loss: 1.0392, Train Accuracy: 0.8694, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9357/10000, Train Loss: 1.0420, Train Accuracy: 0.8717, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9358/10000, Train Loss: 1.0177, Train Accuracy: 0.9007, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9359/10000, Train Loss: 1.0287, Train Accuracy: 0.8761, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9360/10000, Train Loss: 1.0407, Train Accuracy: 0.8717, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9361/10000, Train Loss: 1.0231, Train Accuracy: 0.8828, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 9362/10000, Train Loss: 1.0221, Train Accuracy: 0.8895, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9363/10000, Train Loss: 1.0305, Train Accuracy: 0.8850, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9364/10000, Train Loss: 1.0412, Train Accuracy: 0.8705, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 9365/10000, Train Loss: 1.0321, Train Accuracy: 0.8761, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9366/10000, Train Loss: 1.0431, Train Accuracy: 0.8616, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9367/10000, Train Loss: 1.0267, Train Accuracy: 0.8884, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9368/10000, Train Loss: 1.0236, Train Accuracy: 0.8884, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9369/10000, Train Loss: 1.0330, Train Accuracy: 0.8806, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 9370/10000, Train Loss: 1.0303, Train Accuracy: 0.8717, Val Loss: 1.1763, Val Accuracy: 0.7277
Epoch 9371/10000, Train Loss: 1.0314, Train Accuracy: 0.8817, Val Loss: 1.1764, Val Accuracy: 0.7277
Epoch 9372/10000, Train Loss: 1.0241, Train Accuracy: 0.8873, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 9373/10000, Train Loss: 1.0354, Train Accuracy: 0.8817, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9374/10000, Train Loss: 1.0345, Train Accuracy: 0.8739, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9375/10000, Train Loss: 1.0199, Train Accuracy: 0.8951, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9376/10000, Train Loss: 1.0286, Train Accuracy: 0.8850, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9377/10000, Train Loss: 1.0289, Train Accuracy: 0.8850, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 9378/10000, Train Loss: 1.0351, Train Accuracy: 0.8761, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 9379/10000, Train Loss: 1.0248, Train Accuracy: 0.8850, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 9380/10000, Train Loss: 1.0431, Train Accuracy: 0.8728, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 9381/10000, Train Loss: 1.0360, Train Accuracy: 0.8772, Val Loss: 1.1765, Val Accuracy: 0.7277
Epoch 9382/10000, Train Loss: 1.0316, Train Accuracy: 0.8795, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 9383/10000, Train Loss: 1.0377, Train Accuracy: 0.8772, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 9384/10000, Train Loss: 1.0443, Train Accuracy: 0.8594, Val Loss: 1.1768, Val Accuracy: 0.7321
Epoch 9385/10000, Train Loss: 1.0332, Train Accuracy: 0.8772, Val Loss: 1.1766, Val Accuracy: 0.7277
Epoch 9386/10000, Train Loss: 1.0328, Train Accuracy: 0.8783, Val Loss: 1.1766, Val Accuracy: 0.7321
Epoch 9387/10000, Train Loss: 1.0389, Train Accuracy: 0.8717, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9388/10000, Train Loss: 1.0327, Train Accuracy: 0.8795, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9389/10000, Train Loss: 1.0262, Train Accuracy: 0.8917, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9390/10000, Train Loss: 1.0240, Train Accuracy: 0.8895, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9391/10000, Train Loss: 1.0246, Train Accuracy: 0.8873, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9392/10000, Train Loss: 1.0357, Train Accuracy: 0.8705, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9393/10000, Train Loss: 1.0332, Train Accuracy: 0.8783, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9394/10000, Train Loss: 1.0269, Train Accuracy: 0.8862, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9395/10000, Train Loss: 1.0381, Train Accuracy: 0.8683, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9396/10000, Train Loss: 1.0363, Train Accuracy: 0.8761, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9397/10000, Train Loss: 1.0255, Train Accuracy: 0.8873, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9398/10000, Train Loss: 1.0387, Train Accuracy: 0.8728, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9399/10000, Train Loss: 1.0320, Train Accuracy: 0.8806, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9400/10000, Train Loss: 1.0241, Train Accuracy: 0.8895, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9401/10000, Train Loss: 1.0350, Train Accuracy: 0.8728, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9402/10000, Train Loss: 1.0285, Train Accuracy: 0.8839, Val Loss: 1.1762, Val Accuracy: 0.7321
Epoch 9403/10000, Train Loss: 1.0373, Train Accuracy: 0.8694, Val Loss: 1.1762, Val Accuracy: 0.7277
Epoch 9404/10000, Train Loss: 1.0322, Train Accuracy: 0.8783, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9405/10000, Train Loss: 1.0318, Train Accuracy: 0.8783, Val Loss: 1.1761, Val Accuracy: 0.7277
Epoch 9406/10000, Train Loss: 1.0459, Train Accuracy: 0.8705, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9407/10000, Train Loss: 1.0292, Train Accuracy: 0.8828, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9408/10000, Train Loss: 1.0329, Train Accuracy: 0.8761, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9409/10000, Train Loss: 1.0196, Train Accuracy: 0.8917, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9410/10000, Train Loss: 1.0258, Train Accuracy: 0.8873, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 9411/10000, Train Loss: 1.0276, Train Accuracy: 0.8873, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9412/10000, Train Loss: 1.0197, Train Accuracy: 0.8895, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9413/10000, Train Loss: 1.0356, Train Accuracy: 0.8705, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 9414/10000, Train Loss: 1.0282, Train Accuracy: 0.8839, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9415/10000, Train Loss: 1.0238, Train Accuracy: 0.8906, Val Loss: 1.1761, Val Accuracy: 0.7321
Epoch 9416/10000, Train Loss: 1.0204, Train Accuracy: 0.8940, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9417/10000, Train Loss: 1.0302, Train Accuracy: 0.8828, Val Loss: 1.1758, Val Accuracy: 0.7321
Epoch 9418/10000, Train Loss: 1.0257, Train Accuracy: 0.8850, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9419/10000, Train Loss: 1.0357, Train Accuracy: 0.8739, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9420/10000, Train Loss: 1.0323, Train Accuracy: 0.8850, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 9421/10000, Train Loss: 1.0302, Train Accuracy: 0.8850, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9422/10000, Train Loss: 1.0289, Train Accuracy: 0.8828, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9423/10000, Train Loss: 1.0183, Train Accuracy: 0.8895, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9424/10000, Train Loss: 1.0232, Train Accuracy: 0.8895, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9425/10000, Train Loss: 1.0171, Train Accuracy: 0.8884, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9426/10000, Train Loss: 1.0479, Train Accuracy: 0.8594, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9427/10000, Train Loss: 1.0303, Train Accuracy: 0.8817, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9428/10000, Train Loss: 1.0369, Train Accuracy: 0.8739, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9429/10000, Train Loss: 1.0296, Train Accuracy: 0.8795, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9430/10000, Train Loss: 1.0226, Train Accuracy: 0.8895, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9431/10000, Train Loss: 1.0231, Train Accuracy: 0.8895, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9432/10000, Train Loss: 1.0253, Train Accuracy: 0.8850, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9433/10000, Train Loss: 1.0325, Train Accuracy: 0.8806, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9434/10000, Train Loss: 1.0276, Train Accuracy: 0.8873, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9435/10000, Train Loss: 1.0347, Train Accuracy: 0.8739, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9436/10000, Train Loss: 1.0372, Train Accuracy: 0.8672, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9437/10000, Train Loss: 1.0360, Train Accuracy: 0.8750, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9438/10000, Train Loss: 1.0283, Train Accuracy: 0.8783, Val Loss: 1.1760, Val Accuracy: 0.7277
Epoch 9439/10000, Train Loss: 1.0343, Train Accuracy: 0.8717, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9440/10000, Train Loss: 1.0277, Train Accuracy: 0.8828, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9441/10000, Train Loss: 1.0452, Train Accuracy: 0.8605, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 9442/10000, Train Loss: 1.0268, Train Accuracy: 0.8828, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 9443/10000, Train Loss: 1.0306, Train Accuracy: 0.8783, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9444/10000, Train Loss: 1.0411, Train Accuracy: 0.8650, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9445/10000, Train Loss: 1.0353, Train Accuracy: 0.8783, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9446/10000, Train Loss: 1.0207, Train Accuracy: 0.8873, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9447/10000, Train Loss: 1.0395, Train Accuracy: 0.8717, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9448/10000, Train Loss: 1.0296, Train Accuracy: 0.8795, Val Loss: 1.1758, Val Accuracy: 0.7366
Epoch 9449/10000, Train Loss: 1.0354, Train Accuracy: 0.8694, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 9450/10000, Train Loss: 1.0340, Train Accuracy: 0.8817, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9451/10000, Train Loss: 1.0357, Train Accuracy: 0.8817, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9452/10000, Train Loss: 1.0281, Train Accuracy: 0.8873, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9453/10000, Train Loss: 1.0358, Train Accuracy: 0.8750, Val Loss: 1.1757, Val Accuracy: 0.7366
Epoch 9454/10000, Train Loss: 1.0236, Train Accuracy: 0.8895, Val Loss: 1.1756, Val Accuracy: 0.7366
Epoch 9455/10000, Train Loss: 1.0222, Train Accuracy: 0.8906, Val Loss: 1.1760, Val Accuracy: 0.7321
Epoch 9456/10000, Train Loss: 1.0278, Train Accuracy: 0.8806, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 9457/10000, Train Loss: 1.0304, Train Accuracy: 0.8839, Val Loss: 1.1764, Val Accuracy: 0.7366
Epoch 9458/10000, Train Loss: 1.0347, Train Accuracy: 0.8783, Val Loss: 1.1765, Val Accuracy: 0.7321
Epoch 9459/10000, Train Loss: 1.0240, Train Accuracy: 0.8839, Val Loss: 1.1763, Val Accuracy: 0.7321
Epoch 9460/10000, Train Loss: 1.0300, Train Accuracy: 0.8828, Val Loss: 1.1761, Val Accuracy: 0.7366
Epoch 9461/10000, Train Loss: 1.0306, Train Accuracy: 0.8873, Val Loss: 1.1763, Val Accuracy: 0.7366
Epoch 9462/10000, Train Loss: 1.0328, Train Accuracy: 0.8728, Val Loss: 1.1760, Val Accuracy: 0.7366
Epoch 9463/10000, Train Loss: 1.0263, Train Accuracy: 0.8828, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9464/10000, Train Loss: 1.0313, Train Accuracy: 0.8750, Val Loss: 1.1759, Val Accuracy: 0.7366
Epoch 9465/10000, Train Loss: 1.0380, Train Accuracy: 0.8783, Val Loss: 1.1759, Val Accuracy: 0.7411
Epoch 9466/10000, Train Loss: 1.0332, Train Accuracy: 0.8817, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 9467/10000, Train Loss: 1.0390, Train Accuracy: 0.8638, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 9468/10000, Train Loss: 1.0287, Train Accuracy: 0.8817, Val Loss: 1.1757, Val Accuracy: 0.7411
Epoch 9469/10000, Train Loss: 1.0358, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7411
Epoch 9470/10000, Train Loss: 1.0376, Train Accuracy: 0.8717, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 9471/10000, Train Loss: 1.0325, Train Accuracy: 0.8795, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 9472/10000, Train Loss: 1.0337, Train Accuracy: 0.8761, Val Loss: 1.1750, Val Accuracy: 0.7411
Epoch 9473/10000, Train Loss: 1.0305, Train Accuracy: 0.8761, Val Loss: 1.1749, Val Accuracy: 0.7411
Epoch 9474/10000, Train Loss: 1.0399, Train Accuracy: 0.8672, Val Loss: 1.1749, Val Accuracy: 0.7411
Epoch 9475/10000, Train Loss: 1.0319, Train Accuracy: 0.8795, Val Loss: 1.1750, Val Accuracy: 0.7411
Epoch 9476/10000, Train Loss: 1.0278, Train Accuracy: 0.8884, Val Loss: 1.1751, Val Accuracy: 0.7411
Epoch 9477/10000, Train Loss: 1.0244, Train Accuracy: 0.8929, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 9478/10000, Train Loss: 1.0360, Train Accuracy: 0.8772, Val Loss: 1.1753, Val Accuracy: 0.7411
Epoch 9479/10000, Train Loss: 1.0337, Train Accuracy: 0.8783, Val Loss: 1.1755, Val Accuracy: 0.7411
Epoch 9480/10000, Train Loss: 1.0373, Train Accuracy: 0.8783, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 9481/10000, Train Loss: 1.0206, Train Accuracy: 0.8996, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 9482/10000, Train Loss: 1.0399, Train Accuracy: 0.8750, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 9483/10000, Train Loss: 1.0262, Train Accuracy: 0.8884, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9484/10000, Train Loss: 1.0279, Train Accuracy: 0.8783, Val Loss: 1.1754, Val Accuracy: 0.7411
Epoch 9485/10000, Train Loss: 1.0337, Train Accuracy: 0.8772, Val Loss: 1.1752, Val Accuracy: 0.7411
Epoch 9486/10000, Train Loss: 1.0268, Train Accuracy: 0.8884, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9487/10000, Train Loss: 1.0328, Train Accuracy: 0.8772, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9488/10000, Train Loss: 1.0395, Train Accuracy: 0.8683, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9489/10000, Train Loss: 1.0367, Train Accuracy: 0.8750, Val Loss: 1.1753, Val Accuracy: 0.7366
Epoch 9490/10000, Train Loss: 1.0222, Train Accuracy: 0.8940, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9491/10000, Train Loss: 1.0273, Train Accuracy: 0.8873, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9492/10000, Train Loss: 1.0204, Train Accuracy: 0.8906, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9493/10000, Train Loss: 1.0292, Train Accuracy: 0.8862, Val Loss: 1.1754, Val Accuracy: 0.7366
Epoch 9494/10000, Train Loss: 1.0282, Train Accuracy: 0.8884, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9495/10000, Train Loss: 1.0381, Train Accuracy: 0.8795, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9496/10000, Train Loss: 1.0342, Train Accuracy: 0.8772, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9497/10000, Train Loss: 1.0263, Train Accuracy: 0.8839, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9498/10000, Train Loss: 1.0360, Train Accuracy: 0.8783, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9499/10000, Train Loss: 1.0341, Train Accuracy: 0.8728, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9500/10000, Train Loss: 1.0247, Train Accuracy: 0.8906, Val Loss: 1.1750, Val Accuracy: 0.7366
Epoch 9501/10000, Train Loss: 1.0244, Train Accuracy: 0.8884, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9502/10000, Train Loss: 1.0429, Train Accuracy: 0.8672, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9503/10000, Train Loss: 1.0429, Train Accuracy: 0.8616, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9504/10000, Train Loss: 1.0242, Train Accuracy: 0.8895, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9505/10000, Train Loss: 1.0309, Train Accuracy: 0.8806, Val Loss: 1.1751, Val Accuracy: 0.7366
Epoch 9506/10000, Train Loss: 1.0261, Train Accuracy: 0.8839, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9507/10000, Train Loss: 1.0166, Train Accuracy: 0.8929, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9508/10000, Train Loss: 1.0295, Train Accuracy: 0.8839, Val Loss: 1.1756, Val Accuracy: 0.7277
Epoch 9509/10000, Train Loss: 1.0413, Train Accuracy: 0.8705, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9510/10000, Train Loss: 1.0260, Train Accuracy: 0.8828, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9511/10000, Train Loss: 1.0380, Train Accuracy: 0.8728, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9512/10000, Train Loss: 1.0246, Train Accuracy: 0.8850, Val Loss: 1.1759, Val Accuracy: 0.7277
Epoch 9513/10000, Train Loss: 1.0226, Train Accuracy: 0.8895, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9514/10000, Train Loss: 1.0306, Train Accuracy: 0.8795, Val Loss: 1.1756, Val Accuracy: 0.7277
Epoch 9515/10000, Train Loss: 1.0302, Train Accuracy: 0.8850, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9516/10000, Train Loss: 1.0286, Train Accuracy: 0.8850, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9517/10000, Train Loss: 1.0340, Train Accuracy: 0.8728, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9518/10000, Train Loss: 1.0225, Train Accuracy: 0.8951, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9519/10000, Train Loss: 1.0265, Train Accuracy: 0.8873, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9520/10000, Train Loss: 1.0332, Train Accuracy: 0.8817, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9521/10000, Train Loss: 1.0353, Train Accuracy: 0.8795, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9522/10000, Train Loss: 1.0224, Train Accuracy: 0.8951, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9523/10000, Train Loss: 1.0371, Train Accuracy: 0.8728, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9524/10000, Train Loss: 1.0217, Train Accuracy: 0.8884, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9525/10000, Train Loss: 1.0270, Train Accuracy: 0.8795, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9526/10000, Train Loss: 1.0244, Train Accuracy: 0.8895, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9527/10000, Train Loss: 1.0319, Train Accuracy: 0.8739, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9528/10000, Train Loss: 1.0255, Train Accuracy: 0.8828, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9529/10000, Train Loss: 1.0334, Train Accuracy: 0.8750, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9530/10000, Train Loss: 1.0240, Train Accuracy: 0.8884, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9531/10000, Train Loss: 1.0362, Train Accuracy: 0.8772, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9532/10000, Train Loss: 1.0407, Train Accuracy: 0.8672, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9533/10000, Train Loss: 1.0286, Train Accuracy: 0.8750, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9534/10000, Train Loss: 1.0332, Train Accuracy: 0.8761, Val Loss: 1.1758, Val Accuracy: 0.7277
Epoch 9535/10000, Train Loss: 1.0236, Train Accuracy: 0.8884, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9536/10000, Train Loss: 1.0265, Train Accuracy: 0.8839, Val Loss: 1.1757, Val Accuracy: 0.7277
Epoch 9537/10000, Train Loss: 1.0304, Train Accuracy: 0.8862, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9538/10000, Train Loss: 1.0353, Train Accuracy: 0.8728, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9539/10000, Train Loss: 1.0378, Train Accuracy: 0.8728, Val Loss: 1.1761, Val Accuracy: 0.7232
Epoch 9540/10000, Train Loss: 1.0293, Train Accuracy: 0.8862, Val Loss: 1.1762, Val Accuracy: 0.7188
Epoch 9541/10000, Train Loss: 1.0179, Train Accuracy: 0.8962, Val Loss: 1.1760, Val Accuracy: 0.7188
Epoch 9542/10000, Train Loss: 1.0474, Train Accuracy: 0.8594, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9543/10000, Train Loss: 1.0325, Train Accuracy: 0.8750, Val Loss: 1.1755, Val Accuracy: 0.7232
Epoch 9544/10000, Train Loss: 1.0335, Train Accuracy: 0.8761, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9545/10000, Train Loss: 1.0273, Train Accuracy: 0.8817, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9546/10000, Train Loss: 1.0203, Train Accuracy: 0.8940, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9547/10000, Train Loss: 1.0318, Train Accuracy: 0.8862, Val Loss: 1.1750, Val Accuracy: 0.7232
Epoch 9548/10000, Train Loss: 1.0193, Train Accuracy: 0.8996, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9549/10000, Train Loss: 1.0305, Train Accuracy: 0.8862, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9550/10000, Train Loss: 1.0402, Train Accuracy: 0.8761, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9551/10000, Train Loss: 1.0488, Train Accuracy: 0.8594, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9552/10000, Train Loss: 1.0332, Train Accuracy: 0.8817, Val Loss: 1.1752, Val Accuracy: 0.7232
Epoch 9553/10000, Train Loss: 1.0335, Train Accuracy: 0.8783, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9554/10000, Train Loss: 1.0322, Train Accuracy: 0.8761, Val Loss: 1.1754, Val Accuracy: 0.7232
Epoch 9555/10000, Train Loss: 1.0232, Train Accuracy: 0.8850, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9556/10000, Train Loss: 1.0305, Train Accuracy: 0.8839, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9557/10000, Train Loss: 1.0275, Train Accuracy: 0.8850, Val Loss: 1.1751, Val Accuracy: 0.7321
Epoch 9558/10000, Train Loss: 1.0245, Train Accuracy: 0.8850, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9559/10000, Train Loss: 1.0211, Train Accuracy: 0.8951, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9560/10000, Train Loss: 1.0354, Train Accuracy: 0.8828, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9561/10000, Train Loss: 1.0267, Train Accuracy: 0.8862, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9562/10000, Train Loss: 1.0228, Train Accuracy: 0.8862, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9563/10000, Train Loss: 1.0251, Train Accuracy: 0.8806, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9564/10000, Train Loss: 1.0316, Train Accuracy: 0.8839, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9565/10000, Train Loss: 1.0265, Train Accuracy: 0.8850, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9566/10000, Train Loss: 1.0258, Train Accuracy: 0.8828, Val Loss: 1.1747, Val Accuracy: 0.7277
Epoch 9567/10000, Train Loss: 1.0273, Train Accuracy: 0.8884, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9568/10000, Train Loss: 1.0287, Train Accuracy: 0.8806, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9569/10000, Train Loss: 1.0341, Train Accuracy: 0.8761, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9570/10000, Train Loss: 1.0312, Train Accuracy: 0.8828, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9571/10000, Train Loss: 1.0371, Train Accuracy: 0.8717, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9572/10000, Train Loss: 1.0418, Train Accuracy: 0.8672, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9573/10000, Train Loss: 1.0291, Train Accuracy: 0.8828, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9574/10000, Train Loss: 1.0266, Train Accuracy: 0.8862, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9575/10000, Train Loss: 1.0268, Train Accuracy: 0.8862, Val Loss: 1.1736, Val Accuracy: 0.7321
Epoch 9576/10000, Train Loss: 1.0310, Train Accuracy: 0.8795, Val Loss: 1.1734, Val Accuracy: 0.7321
Epoch 9577/10000, Train Loss: 1.0192, Train Accuracy: 0.8895, Val Loss: 1.1735, Val Accuracy: 0.7321
Epoch 9578/10000, Train Loss: 1.0291, Train Accuracy: 0.8795, Val Loss: 1.1734, Val Accuracy: 0.7321
Epoch 9579/10000, Train Loss: 1.0491, Train Accuracy: 0.8638, Val Loss: 1.1736, Val Accuracy: 0.7321
Epoch 9580/10000, Train Loss: 1.0331, Train Accuracy: 0.8750, Val Loss: 1.1733, Val Accuracy: 0.7321
Epoch 9581/10000, Train Loss: 1.0287, Train Accuracy: 0.8817, Val Loss: 1.1735, Val Accuracy: 0.7321
Epoch 9582/10000, Train Loss: 1.0273, Train Accuracy: 0.8862, Val Loss: 1.1736, Val Accuracy: 0.7321
Epoch 9583/10000, Train Loss: 1.0271, Train Accuracy: 0.8783, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9584/10000, Train Loss: 1.0309, Train Accuracy: 0.8795, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9585/10000, Train Loss: 1.0346, Train Accuracy: 0.8828, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9586/10000, Train Loss: 1.0339, Train Accuracy: 0.8772, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9587/10000, Train Loss: 1.0150, Train Accuracy: 0.8996, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9588/10000, Train Loss: 1.0266, Train Accuracy: 0.8862, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9589/10000, Train Loss: 1.0258, Train Accuracy: 0.8839, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9590/10000, Train Loss: 1.0236, Train Accuracy: 0.8906, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9591/10000, Train Loss: 1.0363, Train Accuracy: 0.8728, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9592/10000, Train Loss: 1.0219, Train Accuracy: 0.8962, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9593/10000, Train Loss: 1.0316, Train Accuracy: 0.8795, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9594/10000, Train Loss: 1.0172, Train Accuracy: 0.8984, Val Loss: 1.1745, Val Accuracy: 0.7277
Epoch 9595/10000, Train Loss: 1.0275, Train Accuracy: 0.8862, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9596/10000, Train Loss: 1.0210, Train Accuracy: 0.8873, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9597/10000, Train Loss: 1.0258, Train Accuracy: 0.8862, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9598/10000, Train Loss: 1.0251, Train Accuracy: 0.8839, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9599/10000, Train Loss: 1.0387, Train Accuracy: 0.8683, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9600/10000, Train Loss: 1.0259, Train Accuracy: 0.8828, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9601/10000, Train Loss: 1.0456, Train Accuracy: 0.8616, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9602/10000, Train Loss: 1.0316, Train Accuracy: 0.8750, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9603/10000, Train Loss: 1.0392, Train Accuracy: 0.8717, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9604/10000, Train Loss: 1.0211, Train Accuracy: 0.8917, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9605/10000, Train Loss: 1.0257, Train Accuracy: 0.8873, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9606/10000, Train Loss: 1.0286, Train Accuracy: 0.8828, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9607/10000, Train Loss: 1.0315, Train Accuracy: 0.8862, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9608/10000, Train Loss: 1.0253, Train Accuracy: 0.8917, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9609/10000, Train Loss: 1.0350, Train Accuracy: 0.8761, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9610/10000, Train Loss: 1.0238, Train Accuracy: 0.8895, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9611/10000, Train Loss: 1.0289, Train Accuracy: 0.8862, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9612/10000, Train Loss: 1.0263, Train Accuracy: 0.8828, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9613/10000, Train Loss: 1.0281, Train Accuracy: 0.8850, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9614/10000, Train Loss: 1.0268, Train Accuracy: 0.8850, Val Loss: 1.1734, Val Accuracy: 0.7366
Epoch 9615/10000, Train Loss: 1.0299, Train Accuracy: 0.8862, Val Loss: 1.1734, Val Accuracy: 0.7321
Epoch 9616/10000, Train Loss: 1.0325, Train Accuracy: 0.8795, Val Loss: 1.1738, Val Accuracy: 0.7321
Epoch 9617/10000, Train Loss: 1.0339, Train Accuracy: 0.8728, Val Loss: 1.1737, Val Accuracy: 0.7321
Epoch 9618/10000, Train Loss: 1.0359, Train Accuracy: 0.8795, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9619/10000, Train Loss: 1.0228, Train Accuracy: 0.8873, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9620/10000, Train Loss: 1.0306, Train Accuracy: 0.8884, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9621/10000, Train Loss: 1.0290, Train Accuracy: 0.8772, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9622/10000, Train Loss: 1.0267, Train Accuracy: 0.8906, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9623/10000, Train Loss: 1.0360, Train Accuracy: 0.8717, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9624/10000, Train Loss: 1.0296, Train Accuracy: 0.8795, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9625/10000, Train Loss: 1.0220, Train Accuracy: 0.8884, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9626/10000, Train Loss: 1.0252, Train Accuracy: 0.8873, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9627/10000, Train Loss: 1.0347, Train Accuracy: 0.8705, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9628/10000, Train Loss: 1.0166, Train Accuracy: 0.8973, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9629/10000, Train Loss: 1.0219, Train Accuracy: 0.8884, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9630/10000, Train Loss: 1.0261, Train Accuracy: 0.8873, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9631/10000, Train Loss: 1.0273, Train Accuracy: 0.8839, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9632/10000, Train Loss: 1.0261, Train Accuracy: 0.8817, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9633/10000, Train Loss: 1.0185, Train Accuracy: 0.8895, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9634/10000, Train Loss: 1.0251, Train Accuracy: 0.8873, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9635/10000, Train Loss: 1.0292, Train Accuracy: 0.8828, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9636/10000, Train Loss: 1.0217, Train Accuracy: 0.8884, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9637/10000, Train Loss: 1.0281, Train Accuracy: 0.8862, Val Loss: 1.1739, Val Accuracy: 0.7277
Epoch 9638/10000, Train Loss: 1.0466, Train Accuracy: 0.8560, Val Loss: 1.1735, Val Accuracy: 0.7277
Epoch 9639/10000, Train Loss: 1.0217, Train Accuracy: 0.8917, Val Loss: 1.1738, Val Accuracy: 0.7277
Epoch 9640/10000, Train Loss: 1.0361, Train Accuracy: 0.8783, Val Loss: 1.1739, Val Accuracy: 0.7277
Epoch 9641/10000, Train Loss: 1.0306, Train Accuracy: 0.8783, Val Loss: 1.1741, Val Accuracy: 0.7277
Epoch 9642/10000, Train Loss: 1.0226, Train Accuracy: 0.8940, Val Loss: 1.1740, Val Accuracy: 0.7277
Epoch 9643/10000, Train Loss: 1.0199, Train Accuracy: 0.8906, Val Loss: 1.1741, Val Accuracy: 0.7277
Epoch 9644/10000, Train Loss: 1.0329, Train Accuracy: 0.8750, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9645/10000, Train Loss: 1.0283, Train Accuracy: 0.8828, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9646/10000, Train Loss: 1.0295, Train Accuracy: 0.8839, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9647/10000, Train Loss: 1.0257, Train Accuracy: 0.8850, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9648/10000, Train Loss: 1.0293, Train Accuracy: 0.8862, Val Loss: 1.1747, Val Accuracy: 0.7277
Epoch 9649/10000, Train Loss: 1.0274, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9650/10000, Train Loss: 1.0265, Train Accuracy: 0.8828, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9651/10000, Train Loss: 1.0335, Train Accuracy: 0.8783, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9652/10000, Train Loss: 1.0294, Train Accuracy: 0.8806, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9653/10000, Train Loss: 1.0218, Train Accuracy: 0.8895, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9654/10000, Train Loss: 1.0369, Train Accuracy: 0.8783, Val Loss: 1.1741, Val Accuracy: 0.7277
Epoch 9655/10000, Train Loss: 1.0148, Train Accuracy: 0.8973, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9656/10000, Train Loss: 1.0244, Train Accuracy: 0.8850, Val Loss: 1.1745, Val Accuracy: 0.7277
Epoch 9657/10000, Train Loss: 1.0322, Train Accuracy: 0.8750, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9658/10000, Train Loss: 1.0237, Train Accuracy: 0.8873, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9659/10000, Train Loss: 1.0345, Train Accuracy: 0.8772, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9660/10000, Train Loss: 1.0341, Train Accuracy: 0.8761, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9661/10000, Train Loss: 1.0269, Train Accuracy: 0.8850, Val Loss: 1.1746, Val Accuracy: 0.7321
Epoch 9662/10000, Train Loss: 1.0395, Train Accuracy: 0.8728, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9663/10000, Train Loss: 1.0320, Train Accuracy: 0.8783, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9664/10000, Train Loss: 1.0216, Train Accuracy: 0.8917, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9665/10000, Train Loss: 1.0291, Train Accuracy: 0.8806, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9666/10000, Train Loss: 1.0232, Train Accuracy: 0.8862, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9667/10000, Train Loss: 1.0250, Train Accuracy: 0.8929, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9668/10000, Train Loss: 1.0309, Train Accuracy: 0.8817, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9669/10000, Train Loss: 1.0274, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9670/10000, Train Loss: 1.0271, Train Accuracy: 0.8806, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9671/10000, Train Loss: 1.0336, Train Accuracy: 0.8783, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9672/10000, Train Loss: 1.0378, Train Accuracy: 0.8728, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9673/10000, Train Loss: 1.0197, Train Accuracy: 0.8962, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9674/10000, Train Loss: 1.0245, Train Accuracy: 0.8873, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9675/10000, Train Loss: 1.0321, Train Accuracy: 0.8750, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9676/10000, Train Loss: 1.0319, Train Accuracy: 0.8817, Val Loss: 1.1747, Val Accuracy: 0.7366
Epoch 9677/10000, Train Loss: 1.0268, Train Accuracy: 0.8884, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9678/10000, Train Loss: 1.0242, Train Accuracy: 0.8795, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9679/10000, Train Loss: 1.0274, Train Accuracy: 0.8884, Val Loss: 1.1754, Val Accuracy: 0.7232
Epoch 9680/10000, Train Loss: 1.0357, Train Accuracy: 0.8772, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9681/10000, Train Loss: 1.0293, Train Accuracy: 0.8817, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9682/10000, Train Loss: 1.0138, Train Accuracy: 0.8940, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9683/10000, Train Loss: 1.0252, Train Accuracy: 0.8817, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9684/10000, Train Loss: 1.0265, Train Accuracy: 0.8862, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9685/10000, Train Loss: 1.0266, Train Accuracy: 0.8828, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9686/10000, Train Loss: 1.0282, Train Accuracy: 0.8795, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9687/10000, Train Loss: 1.0216, Train Accuracy: 0.8906, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9688/10000, Train Loss: 1.0478, Train Accuracy: 0.8638, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9689/10000, Train Loss: 1.0190, Train Accuracy: 0.8984, Val Loss: 1.1754, Val Accuracy: 0.7232
Epoch 9690/10000, Train Loss: 1.0313, Train Accuracy: 0.8783, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9691/10000, Train Loss: 1.0236, Train Accuracy: 0.8929, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9692/10000, Train Loss: 1.0300, Train Accuracy: 0.8772, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9693/10000, Train Loss: 1.0259, Train Accuracy: 0.8850, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9694/10000, Train Loss: 1.0182, Train Accuracy: 0.8973, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9695/10000, Train Loss: 1.0236, Train Accuracy: 0.8951, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9696/10000, Train Loss: 1.0176, Train Accuracy: 0.8940, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9697/10000, Train Loss: 1.0185, Train Accuracy: 0.8940, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9698/10000, Train Loss: 1.0294, Train Accuracy: 0.8817, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9699/10000, Train Loss: 1.0394, Train Accuracy: 0.8683, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9700/10000, Train Loss: 1.0247, Train Accuracy: 0.8850, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9701/10000, Train Loss: 1.0391, Train Accuracy: 0.8705, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9702/10000, Train Loss: 1.0393, Train Accuracy: 0.8683, Val Loss: 1.1755, Val Accuracy: 0.7232
Epoch 9703/10000, Train Loss: 1.0214, Train Accuracy: 0.8929, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9704/10000, Train Loss: 1.0235, Train Accuracy: 0.8940, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9705/10000, Train Loss: 1.0212, Train Accuracy: 0.8884, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9706/10000, Train Loss: 1.0248, Train Accuracy: 0.8850, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9707/10000, Train Loss: 1.0404, Train Accuracy: 0.8661, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9708/10000, Train Loss: 1.0233, Train Accuracy: 0.8884, Val Loss: 1.1747, Val Accuracy: 0.7277
Epoch 9709/10000, Train Loss: 1.0251, Train Accuracy: 0.8828, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9710/10000, Train Loss: 1.0347, Train Accuracy: 0.8817, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9711/10000, Train Loss: 1.0168, Train Accuracy: 0.9018, Val Loss: 1.1745, Val Accuracy: 0.7277
Epoch 9712/10000, Train Loss: 1.0230, Train Accuracy: 0.8862, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9713/10000, Train Loss: 1.0398, Train Accuracy: 0.8717, Val Loss: 1.1747, Val Accuracy: 0.7277
Epoch 9714/10000, Train Loss: 1.0226, Train Accuracy: 0.8884, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9715/10000, Train Loss: 1.0347, Train Accuracy: 0.8806, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9716/10000, Train Loss: 1.0314, Train Accuracy: 0.8772, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9717/10000, Train Loss: 1.0209, Train Accuracy: 0.8940, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9718/10000, Train Loss: 1.0290, Train Accuracy: 0.8839, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9719/10000, Train Loss: 1.0399, Train Accuracy: 0.8661, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9720/10000, Train Loss: 1.0177, Train Accuracy: 0.8951, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9721/10000, Train Loss: 1.0228, Train Accuracy: 0.8862, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9722/10000, Train Loss: 1.0169, Train Accuracy: 0.8906, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9723/10000, Train Loss: 1.0435, Train Accuracy: 0.8616, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9724/10000, Train Loss: 1.0201, Train Accuracy: 0.8951, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9725/10000, Train Loss: 1.0189, Train Accuracy: 0.8906, Val Loss: 1.1749, Val Accuracy: 0.7366
Epoch 9726/10000, Train Loss: 1.0312, Train Accuracy: 0.8772, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9727/10000, Train Loss: 1.0412, Train Accuracy: 0.8705, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9728/10000, Train Loss: 1.0277, Train Accuracy: 0.8795, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9729/10000, Train Loss: 1.0223, Train Accuracy: 0.8917, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9730/10000, Train Loss: 1.0279, Train Accuracy: 0.8817, Val Loss: 1.1744, Val Accuracy: 0.7366
Epoch 9731/10000, Train Loss: 1.0299, Train Accuracy: 0.8817, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9732/10000, Train Loss: 1.0335, Train Accuracy: 0.8772, Val Loss: 1.1742, Val Accuracy: 0.7366
Epoch 9733/10000, Train Loss: 1.0219, Train Accuracy: 0.8951, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9734/10000, Train Loss: 1.0263, Train Accuracy: 0.8873, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9735/10000, Train Loss: 1.0228, Train Accuracy: 0.8984, Val Loss: 1.1744, Val Accuracy: 0.7277
Epoch 9736/10000, Train Loss: 1.0321, Train Accuracy: 0.8795, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9737/10000, Train Loss: 1.0233, Train Accuracy: 0.8873, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9738/10000, Train Loss: 1.0283, Train Accuracy: 0.8839, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9739/10000, Train Loss: 1.0319, Train Accuracy: 0.8850, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9740/10000, Train Loss: 1.0283, Train Accuracy: 0.8817, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9741/10000, Train Loss: 1.0145, Train Accuracy: 0.9029, Val Loss: 1.1745, Val Accuracy: 0.7321
Epoch 9742/10000, Train Loss: 1.0363, Train Accuracy: 0.8750, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9743/10000, Train Loss: 1.0410, Train Accuracy: 0.8705, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9744/10000, Train Loss: 1.0257, Train Accuracy: 0.8862, Val Loss: 1.1744, Val Accuracy: 0.7321
Epoch 9745/10000, Train Loss: 1.0306, Train Accuracy: 0.8772, Val Loss: 1.1748, Val Accuracy: 0.7321
Epoch 9746/10000, Train Loss: 1.0284, Train Accuracy: 0.8862, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9747/10000, Train Loss: 1.0217, Train Accuracy: 0.8929, Val Loss: 1.1748, Val Accuracy: 0.7366
Epoch 9748/10000, Train Loss: 1.0312, Train Accuracy: 0.8839, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9749/10000, Train Loss: 1.0293, Train Accuracy: 0.8795, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9750/10000, Train Loss: 1.0341, Train Accuracy: 0.8795, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9751/10000, Train Loss: 1.0262, Train Accuracy: 0.8839, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9752/10000, Train Loss: 1.0275, Train Accuracy: 0.8806, Val Loss: 1.1756, Val Accuracy: 0.7277
Epoch 9753/10000, Train Loss: 1.0142, Train Accuracy: 0.8962, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9754/10000, Train Loss: 1.0278, Train Accuracy: 0.8839, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9755/10000, Train Loss: 1.0325, Train Accuracy: 0.8772, Val Loss: 1.1756, Val Accuracy: 0.7277
Epoch 9756/10000, Train Loss: 1.0217, Train Accuracy: 0.8951, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9757/10000, Train Loss: 1.0367, Train Accuracy: 0.8683, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9758/10000, Train Loss: 1.0337, Train Accuracy: 0.8717, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9759/10000, Train Loss: 1.0346, Train Accuracy: 0.8772, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9760/10000, Train Loss: 1.0333, Train Accuracy: 0.8783, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9761/10000, Train Loss: 1.0270, Train Accuracy: 0.8873, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9762/10000, Train Loss: 1.0206, Train Accuracy: 0.8929, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9763/10000, Train Loss: 1.0360, Train Accuracy: 0.8772, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9764/10000, Train Loss: 1.0212, Train Accuracy: 0.8951, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9765/10000, Train Loss: 1.0334, Train Accuracy: 0.8783, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9766/10000, Train Loss: 1.0236, Train Accuracy: 0.8862, Val Loss: 1.1759, Val Accuracy: 0.7188
Epoch 9767/10000, Train Loss: 1.0205, Train Accuracy: 0.8962, Val Loss: 1.1761, Val Accuracy: 0.7188
Epoch 9768/10000, Train Loss: 1.0242, Train Accuracy: 0.8806, Val Loss: 1.1761, Val Accuracy: 0.7188
Epoch 9769/10000, Train Loss: 1.0256, Train Accuracy: 0.8839, Val Loss: 1.1759, Val Accuracy: 0.7188
Epoch 9770/10000, Train Loss: 1.0123, Train Accuracy: 0.8996, Val Loss: 1.1763, Val Accuracy: 0.7188
Epoch 9771/10000, Train Loss: 1.0347, Train Accuracy: 0.8739, Val Loss: 1.1764, Val Accuracy: 0.7188
Epoch 9772/10000, Train Loss: 1.0334, Train Accuracy: 0.8761, Val Loss: 1.1762, Val Accuracy: 0.7188
Epoch 9773/10000, Train Loss: 1.0170, Train Accuracy: 0.9018, Val Loss: 1.1762, Val Accuracy: 0.7188
Epoch 9774/10000, Train Loss: 1.0254, Train Accuracy: 0.8839, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9775/10000, Train Loss: 1.0385, Train Accuracy: 0.8772, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9776/10000, Train Loss: 1.0292, Train Accuracy: 0.8761, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9777/10000, Train Loss: 1.0350, Train Accuracy: 0.8761, Val Loss: 1.1756, Val Accuracy: 0.7188
Epoch 9778/10000, Train Loss: 1.0240, Train Accuracy: 0.8817, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9779/10000, Train Loss: 1.0192, Train Accuracy: 0.8962, Val Loss: 1.1756, Val Accuracy: 0.7232
Epoch 9780/10000, Train Loss: 1.0287, Train Accuracy: 0.8873, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9781/10000, Train Loss: 1.0164, Train Accuracy: 0.8951, Val Loss: 1.1756, Val Accuracy: 0.7321
Epoch 9782/10000, Train Loss: 1.0177, Train Accuracy: 0.8940, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9783/10000, Train Loss: 1.0356, Train Accuracy: 0.8717, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9784/10000, Train Loss: 1.0231, Train Accuracy: 0.8806, Val Loss: 1.1757, Val Accuracy: 0.7321
Epoch 9785/10000, Train Loss: 1.0172, Train Accuracy: 0.8951, Val Loss: 1.1759, Val Accuracy: 0.7321
Epoch 9786/10000, Train Loss: 1.0227, Train Accuracy: 0.8839, Val Loss: 1.1755, Val Accuracy: 0.7321
Epoch 9787/10000, Train Loss: 1.0177, Train Accuracy: 0.8884, Val Loss: 1.1753, Val Accuracy: 0.7321
Epoch 9788/10000, Train Loss: 1.0158, Train Accuracy: 0.9051, Val Loss: 1.1754, Val Accuracy: 0.7321
Epoch 9789/10000, Train Loss: 1.0334, Train Accuracy: 0.8783, Val Loss: 1.1750, Val Accuracy: 0.7321
Epoch 9790/10000, Train Loss: 1.0204, Train Accuracy: 0.8862, Val Loss: 1.1749, Val Accuracy: 0.7321
Epoch 9791/10000, Train Loss: 1.0217, Train Accuracy: 0.8884, Val Loss: 1.1752, Val Accuracy: 0.7321
Epoch 9792/10000, Train Loss: 1.0259, Train Accuracy: 0.8884, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9793/10000, Train Loss: 1.0236, Train Accuracy: 0.8850, Val Loss: 1.1758, Val Accuracy: 0.7232
Epoch 9794/10000, Train Loss: 1.0303, Train Accuracy: 0.8795, Val Loss: 1.1758, Val Accuracy: 0.7188
Epoch 9795/10000, Train Loss: 1.0260, Train Accuracy: 0.8862, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9796/10000, Train Loss: 1.0251, Train Accuracy: 0.8873, Val Loss: 1.1755, Val Accuracy: 0.7277
Epoch 9797/10000, Train Loss: 1.0316, Train Accuracy: 0.8783, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9798/10000, Train Loss: 1.0178, Train Accuracy: 0.8917, Val Loss: 1.1760, Val Accuracy: 0.7188
Epoch 9799/10000, Train Loss: 1.0222, Train Accuracy: 0.8884, Val Loss: 1.1760, Val Accuracy: 0.7232
Epoch 9800/10000, Train Loss: 1.0253, Train Accuracy: 0.8917, Val Loss: 1.1760, Val Accuracy: 0.7188
Epoch 9801/10000, Train Loss: 1.0331, Train Accuracy: 0.8817, Val Loss: 1.1759, Val Accuracy: 0.7232
Epoch 9802/10000, Train Loss: 1.0250, Train Accuracy: 0.8862, Val Loss: 1.1757, Val Accuracy: 0.7232
Epoch 9803/10000, Train Loss: 1.0306, Train Accuracy: 0.8828, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9804/10000, Train Loss: 1.0258, Train Accuracy: 0.8839, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9805/10000, Train Loss: 1.0244, Train Accuracy: 0.8884, Val Loss: 1.1758, Val Accuracy: 0.7188
Epoch 9806/10000, Train Loss: 1.0292, Train Accuracy: 0.8817, Val Loss: 1.1759, Val Accuracy: 0.7188
Epoch 9807/10000, Train Loss: 1.0287, Train Accuracy: 0.8806, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9808/10000, Train Loss: 1.0229, Train Accuracy: 0.8906, Val Loss: 1.1755, Val Accuracy: 0.7188
Epoch 9809/10000, Train Loss: 1.0244, Train Accuracy: 0.8828, Val Loss: 1.1755, Val Accuracy: 0.7188
Epoch 9810/10000, Train Loss: 1.0213, Train Accuracy: 0.8884, Val Loss: 1.1753, Val Accuracy: 0.7232
Epoch 9811/10000, Train Loss: 1.0236, Train Accuracy: 0.8873, Val Loss: 1.1754, Val Accuracy: 0.7188
Epoch 9812/10000, Train Loss: 1.0323, Train Accuracy: 0.8672, Val Loss: 1.1756, Val Accuracy: 0.7188
Epoch 9813/10000, Train Loss: 1.0188, Train Accuracy: 0.8929, Val Loss: 1.1757, Val Accuracy: 0.7188
Epoch 9814/10000, Train Loss: 1.0310, Train Accuracy: 0.8783, Val Loss: 1.1755, Val Accuracy: 0.7232
Epoch 9815/10000, Train Loss: 1.0178, Train Accuracy: 0.8917, Val Loss: 1.1755, Val Accuracy: 0.7188
Epoch 9816/10000, Train Loss: 1.0191, Train Accuracy: 0.8929, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9817/10000, Train Loss: 1.0269, Train Accuracy: 0.8850, Val Loss: 1.1754, Val Accuracy: 0.7188
Epoch 9818/10000, Train Loss: 1.0220, Train Accuracy: 0.8951, Val Loss: 1.1752, Val Accuracy: 0.7277
Epoch 9819/10000, Train Loss: 1.0290, Train Accuracy: 0.8828, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9820/10000, Train Loss: 1.0245, Train Accuracy: 0.8895, Val Loss: 1.1753, Val Accuracy: 0.7232
Epoch 9821/10000, Train Loss: 1.0148, Train Accuracy: 0.8951, Val Loss: 1.1753, Val Accuracy: 0.7232
Epoch 9822/10000, Train Loss: 1.0244, Train Accuracy: 0.8828, Val Loss: 1.1754, Val Accuracy: 0.7277
Epoch 9823/10000, Train Loss: 1.0256, Train Accuracy: 0.8850, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9824/10000, Train Loss: 1.0321, Train Accuracy: 0.8750, Val Loss: 1.1751, Val Accuracy: 0.7277
Epoch 9825/10000, Train Loss: 1.0274, Train Accuracy: 0.8828, Val Loss: 1.1751, Val Accuracy: 0.7232
Epoch 9826/10000, Train Loss: 1.0260, Train Accuracy: 0.8906, Val Loss: 1.1753, Val Accuracy: 0.7143
Epoch 9827/10000, Train Loss: 1.0266, Train Accuracy: 0.8839, Val Loss: 1.1753, Val Accuracy: 0.7188
Epoch 9828/10000, Train Loss: 1.0162, Train Accuracy: 0.9007, Val Loss: 1.1757, Val Accuracy: 0.7143
Epoch 9829/10000, Train Loss: 1.0205, Train Accuracy: 0.8873, Val Loss: 1.1755, Val Accuracy: 0.7232
Epoch 9830/10000, Train Loss: 1.0203, Train Accuracy: 0.8884, Val Loss: 1.1757, Val Accuracy: 0.7143
Epoch 9831/10000, Train Loss: 1.0231, Train Accuracy: 0.8895, Val Loss: 1.1754, Val Accuracy: 0.7143
Epoch 9832/10000, Train Loss: 1.0308, Train Accuracy: 0.8806, Val Loss: 1.1753, Val Accuracy: 0.7143
Epoch 9833/10000, Train Loss: 1.0316, Train Accuracy: 0.8772, Val Loss: 1.1755, Val Accuracy: 0.7188
Epoch 9834/10000, Train Loss: 1.0215, Train Accuracy: 0.8906, Val Loss: 1.1752, Val Accuracy: 0.7143
Epoch 9835/10000, Train Loss: 1.0164, Train Accuracy: 0.8884, Val Loss: 1.1753, Val Accuracy: 0.7188
Epoch 9836/10000, Train Loss: 1.0272, Train Accuracy: 0.8862, Val Loss: 1.1748, Val Accuracy: 0.7188
Epoch 9837/10000, Train Loss: 1.0248, Train Accuracy: 0.8873, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9838/10000, Train Loss: 1.0256, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7232
Epoch 9839/10000, Train Loss: 1.0232, Train Accuracy: 0.8895, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9840/10000, Train Loss: 1.0340, Train Accuracy: 0.8728, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9841/10000, Train Loss: 1.0180, Train Accuracy: 0.8951, Val Loss: 1.1744, Val Accuracy: 0.7277
Epoch 9842/10000, Train Loss: 1.0277, Train Accuracy: 0.8873, Val Loss: 1.1743, Val Accuracy: 0.7366
Epoch 9843/10000, Train Loss: 1.0201, Train Accuracy: 0.8917, Val Loss: 1.1742, Val Accuracy: 0.7321
Epoch 9844/10000, Train Loss: 1.0305, Train Accuracy: 0.8806, Val Loss: 1.1742, Val Accuracy: 0.7366
Epoch 9845/10000, Train Loss: 1.0152, Train Accuracy: 0.9007, Val Loss: 1.1740, Val Accuracy: 0.7366
Epoch 9846/10000, Train Loss: 1.0230, Train Accuracy: 0.8828, Val Loss: 1.1739, Val Accuracy: 0.7366
Epoch 9847/10000, Train Loss: 1.0359, Train Accuracy: 0.8761, Val Loss: 1.1742, Val Accuracy: 0.7277
Epoch 9848/10000, Train Loss: 1.0264, Train Accuracy: 0.8917, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9849/10000, Train Loss: 1.0233, Train Accuracy: 0.8906, Val Loss: 1.1741, Val Accuracy: 0.7366
Epoch 9850/10000, Train Loss: 1.0121, Train Accuracy: 0.9007, Val Loss: 1.1739, Val Accuracy: 0.7366
Epoch 9851/10000, Train Loss: 1.0194, Train Accuracy: 0.8873, Val Loss: 1.1741, Val Accuracy: 0.7277
Epoch 9852/10000, Train Loss: 1.0203, Train Accuracy: 0.8873, Val Loss: 1.1742, Val Accuracy: 0.7277
Epoch 9853/10000, Train Loss: 1.0261, Train Accuracy: 0.8761, Val Loss: 1.1742, Val Accuracy: 0.7277
Epoch 9854/10000, Train Loss: 1.0232, Train Accuracy: 0.8884, Val Loss: 1.1739, Val Accuracy: 0.7277
Epoch 9855/10000, Train Loss: 1.0172, Train Accuracy: 0.8951, Val Loss: 1.1739, Val Accuracy: 0.7232
Epoch 9856/10000, Train Loss: 1.0195, Train Accuracy: 0.8962, Val Loss: 1.1737, Val Accuracy: 0.7232
Epoch 9857/10000, Train Loss: 1.0267, Train Accuracy: 0.8873, Val Loss: 1.1734, Val Accuracy: 0.7277
Epoch 9858/10000, Train Loss: 1.0361, Train Accuracy: 0.8705, Val Loss: 1.1737, Val Accuracy: 0.7188
Epoch 9859/10000, Train Loss: 1.0286, Train Accuracy: 0.8817, Val Loss: 1.1736, Val Accuracy: 0.7232
Epoch 9860/10000, Train Loss: 1.0324, Train Accuracy: 0.8806, Val Loss: 1.1737, Val Accuracy: 0.7232
Epoch 9861/10000, Train Loss: 1.0272, Train Accuracy: 0.8839, Val Loss: 1.1739, Val Accuracy: 0.7188
Epoch 9862/10000, Train Loss: 1.0281, Train Accuracy: 0.8850, Val Loss: 1.1737, Val Accuracy: 0.7232
Epoch 9863/10000, Train Loss: 1.0341, Train Accuracy: 0.8728, Val Loss: 1.1737, Val Accuracy: 0.7232
Epoch 9864/10000, Train Loss: 1.0306, Train Accuracy: 0.8839, Val Loss: 1.1738, Val Accuracy: 0.7232
Epoch 9865/10000, Train Loss: 1.0327, Train Accuracy: 0.8772, Val Loss: 1.1737, Val Accuracy: 0.7188
Epoch 9866/10000, Train Loss: 1.0214, Train Accuracy: 0.8884, Val Loss: 1.1739, Val Accuracy: 0.7188
Epoch 9867/10000, Train Loss: 1.0259, Train Accuracy: 0.8873, Val Loss: 1.1740, Val Accuracy: 0.7188
Epoch 9868/10000, Train Loss: 1.0275, Train Accuracy: 0.8839, Val Loss: 1.1742, Val Accuracy: 0.7143
Epoch 9869/10000, Train Loss: 1.0238, Train Accuracy: 0.8850, Val Loss: 1.1741, Val Accuracy: 0.7188
Epoch 9870/10000, Train Loss: 1.0175, Train Accuracy: 0.8951, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9871/10000, Train Loss: 1.0245, Train Accuracy: 0.8828, Val Loss: 1.1743, Val Accuracy: 0.7188
Epoch 9872/10000, Train Loss: 1.0211, Train Accuracy: 0.8929, Val Loss: 1.1744, Val Accuracy: 0.7143
Epoch 9873/10000, Train Loss: 1.0228, Train Accuracy: 0.8917, Val Loss: 1.1746, Val Accuracy: 0.7188
Epoch 9874/10000, Train Loss: 1.0325, Train Accuracy: 0.8750, Val Loss: 1.1742, Val Accuracy: 0.7188
Epoch 9875/10000, Train Loss: 1.0139, Train Accuracy: 0.8984, Val Loss: 1.1743, Val Accuracy: 0.7232
Epoch 9876/10000, Train Loss: 1.0262, Train Accuracy: 0.8873, Val Loss: 1.1743, Val Accuracy: 0.7232
Epoch 9877/10000, Train Loss: 1.0164, Train Accuracy: 0.8929, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9878/10000, Train Loss: 1.0192, Train Accuracy: 0.8940, Val Loss: 1.1745, Val Accuracy: 0.7143
Epoch 9879/10000, Train Loss: 1.0293, Train Accuracy: 0.8750, Val Loss: 1.1745, Val Accuracy: 0.7188
Epoch 9880/10000, Train Loss: 1.0301, Train Accuracy: 0.8795, Val Loss: 1.1748, Val Accuracy: 0.7188
Epoch 9881/10000, Train Loss: 1.0333, Train Accuracy: 0.8761, Val Loss: 1.1746, Val Accuracy: 0.7143
Epoch 9882/10000, Train Loss: 1.0351, Train Accuracy: 0.8772, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9883/10000, Train Loss: 1.0121, Train Accuracy: 0.8973, Val Loss: 1.1750, Val Accuracy: 0.7188
Epoch 9884/10000, Train Loss: 1.0059, Train Accuracy: 0.9074, Val Loss: 1.1750, Val Accuracy: 0.7188
Epoch 9885/10000, Train Loss: 1.0295, Train Accuracy: 0.8806, Val Loss: 1.1751, Val Accuracy: 0.7188
Epoch 9886/10000, Train Loss: 1.0259, Train Accuracy: 0.8862, Val Loss: 1.1754, Val Accuracy: 0.7143
Epoch 9887/10000, Train Loss: 1.0213, Train Accuracy: 0.8873, Val Loss: 1.1751, Val Accuracy: 0.7188
Epoch 9888/10000, Train Loss: 1.0147, Train Accuracy: 0.8996, Val Loss: 1.1749, Val Accuracy: 0.7232
Epoch 9889/10000, Train Loss: 1.0176, Train Accuracy: 0.8940, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9890/10000, Train Loss: 1.0266, Train Accuracy: 0.8862, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9891/10000, Train Loss: 1.0168, Train Accuracy: 0.8984, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9892/10000, Train Loss: 1.0275, Train Accuracy: 0.8862, Val Loss: 1.1746, Val Accuracy: 0.7232
Epoch 9893/10000, Train Loss: 1.0089, Train Accuracy: 0.9040, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9894/10000, Train Loss: 1.0215, Train Accuracy: 0.8884, Val Loss: 1.1749, Val Accuracy: 0.7232
Epoch 9895/10000, Train Loss: 1.0276, Train Accuracy: 0.8850, Val Loss: 1.1748, Val Accuracy: 0.7232
Epoch 9896/10000, Train Loss: 1.0206, Train Accuracy: 0.8951, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9897/10000, Train Loss: 1.0218, Train Accuracy: 0.8884, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9898/10000, Train Loss: 1.0205, Train Accuracy: 0.8906, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9899/10000, Train Loss: 1.0227, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7277
Epoch 9900/10000, Train Loss: 1.0190, Train Accuracy: 0.8862, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9901/10000, Train Loss: 1.0213, Train Accuracy: 0.8862, Val Loss: 1.1753, Val Accuracy: 0.7277
Epoch 9902/10000, Train Loss: 1.0357, Train Accuracy: 0.8761, Val Loss: 1.1750, Val Accuracy: 0.7277
Epoch 9903/10000, Train Loss: 1.0300, Train Accuracy: 0.8828, Val Loss: 1.1749, Val Accuracy: 0.7277
Epoch 9904/10000, Train Loss: 1.0162, Train Accuracy: 0.8984, Val Loss: 1.1747, Val Accuracy: 0.7277
Epoch 9905/10000, Train Loss: 1.0200, Train Accuracy: 0.8895, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9906/10000, Train Loss: 1.0282, Train Accuracy: 0.8828, Val Loss: 1.1746, Val Accuracy: 0.7232
Epoch 9907/10000, Train Loss: 1.0142, Train Accuracy: 0.9018, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9908/10000, Train Loss: 1.0185, Train Accuracy: 0.8962, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9909/10000, Train Loss: 1.0171, Train Accuracy: 0.8984, Val Loss: 1.1747, Val Accuracy: 0.7321
Epoch 9910/10000, Train Loss: 1.0186, Train Accuracy: 0.9018, Val Loss: 1.1746, Val Accuracy: 0.7277
Epoch 9911/10000, Train Loss: 1.0254, Train Accuracy: 0.8839, Val Loss: 1.1744, Val Accuracy: 0.7277
Epoch 9912/10000, Train Loss: 1.0215, Train Accuracy: 0.8895, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9913/10000, Train Loss: 1.0157, Train Accuracy: 0.9029, Val Loss: 1.1740, Val Accuracy: 0.7277
Epoch 9914/10000, Train Loss: 1.0282, Train Accuracy: 0.8806, Val Loss: 1.1737, Val Accuracy: 0.7277
Epoch 9915/10000, Train Loss: 1.0207, Train Accuracy: 0.8962, Val Loss: 1.1739, Val Accuracy: 0.7321
Epoch 9916/10000, Train Loss: 1.0286, Train Accuracy: 0.8850, Val Loss: 1.1741, Val Accuracy: 0.7321
Epoch 9917/10000, Train Loss: 1.0223, Train Accuracy: 0.8929, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9918/10000, Train Loss: 1.0326, Train Accuracy: 0.8783, Val Loss: 1.1744, Val Accuracy: 0.7277
Epoch 9919/10000, Train Loss: 1.0216, Train Accuracy: 0.8906, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9920/10000, Train Loss: 1.0291, Train Accuracy: 0.8772, Val Loss: 1.1740, Val Accuracy: 0.7321
Epoch 9921/10000, Train Loss: 1.0249, Train Accuracy: 0.8839, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9922/10000, Train Loss: 1.0218, Train Accuracy: 0.8850, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9923/10000, Train Loss: 1.0344, Train Accuracy: 0.8728, Val Loss: 1.1745, Val Accuracy: 0.7277
Epoch 9924/10000, Train Loss: 1.0104, Train Accuracy: 0.9051, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9925/10000, Train Loss: 1.0216, Train Accuracy: 0.8873, Val Loss: 1.1742, Val Accuracy: 0.7277
Epoch 9926/10000, Train Loss: 1.0094, Train Accuracy: 0.9074, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9927/10000, Train Loss: 1.0255, Train Accuracy: 0.8884, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9928/10000, Train Loss: 1.0191, Train Accuracy: 0.8895, Val Loss: 1.1744, Val Accuracy: 0.7232
Epoch 9929/10000, Train Loss: 1.0285, Train Accuracy: 0.8817, Val Loss: 1.1744, Val Accuracy: 0.7232
Epoch 9930/10000, Train Loss: 1.0218, Train Accuracy: 0.8895, Val Loss: 1.1743, Val Accuracy: 0.7321
Epoch 9931/10000, Train Loss: 1.0174, Train Accuracy: 0.8951, Val Loss: 1.1743, Val Accuracy: 0.7188
Epoch 9932/10000, Train Loss: 1.0150, Train Accuracy: 0.8951, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9933/10000, Train Loss: 1.0276, Train Accuracy: 0.8761, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9934/10000, Train Loss: 1.0258, Train Accuracy: 0.8783, Val Loss: 1.1747, Val Accuracy: 0.7143
Epoch 9935/10000, Train Loss: 1.0242, Train Accuracy: 0.8850, Val Loss: 1.1745, Val Accuracy: 0.7188
Epoch 9936/10000, Train Loss: 1.0219, Train Accuracy: 0.8929, Val Loss: 1.1742, Val Accuracy: 0.7188
Epoch 9937/10000, Train Loss: 1.0302, Train Accuracy: 0.8806, Val Loss: 1.1746, Val Accuracy: 0.7143
Epoch 9938/10000, Train Loss: 1.0114, Train Accuracy: 0.8996, Val Loss: 1.1743, Val Accuracy: 0.7188
Epoch 9939/10000, Train Loss: 1.0192, Train Accuracy: 0.8962, Val Loss: 1.1745, Val Accuracy: 0.7188
Epoch 9940/10000, Train Loss: 1.0265, Train Accuracy: 0.8795, Val Loss: 1.1745, Val Accuracy: 0.7188
Epoch 9941/10000, Train Loss: 1.0143, Train Accuracy: 0.8984, Val Loss: 1.1745, Val Accuracy: 0.7143
Epoch 9942/10000, Train Loss: 1.0208, Train Accuracy: 0.8884, Val Loss: 1.1746, Val Accuracy: 0.7143
Epoch 9943/10000, Train Loss: 1.0289, Train Accuracy: 0.8795, Val Loss: 1.1747, Val Accuracy: 0.7143
Epoch 9944/10000, Train Loss: 1.0251, Train Accuracy: 0.8850, Val Loss: 1.1744, Val Accuracy: 0.7143
Epoch 9945/10000, Train Loss: 1.0287, Train Accuracy: 0.8806, Val Loss: 1.1740, Val Accuracy: 0.7143
Epoch 9946/10000, Train Loss: 1.0168, Train Accuracy: 0.8996, Val Loss: 1.1739, Val Accuracy: 0.7188
Epoch 9947/10000, Train Loss: 1.0186, Train Accuracy: 0.8984, Val Loss: 1.1738, Val Accuracy: 0.7188
Epoch 9948/10000, Train Loss: 1.0251, Train Accuracy: 0.8806, Val Loss: 1.1736, Val Accuracy: 0.7188
Epoch 9949/10000, Train Loss: 1.0256, Train Accuracy: 0.8817, Val Loss: 1.1735, Val Accuracy: 0.7277
Epoch 9950/10000, Train Loss: 1.0234, Train Accuracy: 0.8839, Val Loss: 1.1736, Val Accuracy: 0.7277
Epoch 9951/10000, Train Loss: 1.0243, Train Accuracy: 0.8895, Val Loss: 1.1736, Val Accuracy: 0.7277
Epoch 9952/10000, Train Loss: 1.0083, Train Accuracy: 0.9029, Val Loss: 1.1737, Val Accuracy: 0.7277
Epoch 9953/10000, Train Loss: 1.0248, Train Accuracy: 0.8850, Val Loss: 1.1738, Val Accuracy: 0.7232
Epoch 9954/10000, Train Loss: 1.0239, Train Accuracy: 0.8850, Val Loss: 1.1736, Val Accuracy: 0.7277
Epoch 9955/10000, Train Loss: 1.0303, Train Accuracy: 0.8806, Val Loss: 1.1735, Val Accuracy: 0.7277
Epoch 9956/10000, Train Loss: 1.0148, Train Accuracy: 0.8973, Val Loss: 1.1738, Val Accuracy: 0.7277
Epoch 9957/10000, Train Loss: 1.0207, Train Accuracy: 0.8917, Val Loss: 1.1738, Val Accuracy: 0.7232
Epoch 9958/10000, Train Loss: 1.0170, Train Accuracy: 0.9007, Val Loss: 1.1738, Val Accuracy: 0.7232
Epoch 9959/10000, Train Loss: 1.0234, Train Accuracy: 0.8895, Val Loss: 1.1736, Val Accuracy: 0.7277
Epoch 9960/10000, Train Loss: 1.0217, Train Accuracy: 0.8873, Val Loss: 1.1737, Val Accuracy: 0.7277
Epoch 9961/10000, Train Loss: 1.0205, Train Accuracy: 0.8884, Val Loss: 1.1738, Val Accuracy: 0.7232
Epoch 9962/10000, Train Loss: 1.0146, Train Accuracy: 0.9018, Val Loss: 1.1741, Val Accuracy: 0.7277
Epoch 9963/10000, Train Loss: 1.0227, Train Accuracy: 0.8940, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9964/10000, Train Loss: 1.0252, Train Accuracy: 0.8862, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9965/10000, Train Loss: 1.0147, Train Accuracy: 0.8951, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9966/10000, Train Loss: 1.0205, Train Accuracy: 0.8929, Val Loss: 1.1748, Val Accuracy: 0.7188
Epoch 9967/10000, Train Loss: 1.0244, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7188
Epoch 9968/10000, Train Loss: 1.0170, Train Accuracy: 0.8951, Val Loss: 1.1749, Val Accuracy: 0.7188
Epoch 9969/10000, Train Loss: 1.0251, Train Accuracy: 0.8828, Val Loss: 1.1748, Val Accuracy: 0.7188
Epoch 9970/10000, Train Loss: 1.0128, Train Accuracy: 0.9007, Val Loss: 1.1751, Val Accuracy: 0.7143
Epoch 9971/10000, Train Loss: 1.0299, Train Accuracy: 0.8806, Val Loss: 1.1751, Val Accuracy: 0.7143
Epoch 9972/10000, Train Loss: 1.0283, Train Accuracy: 0.8750, Val Loss: 1.1752, Val Accuracy: 0.7143
Epoch 9973/10000, Train Loss: 1.0452, Train Accuracy: 0.8683, Val Loss: 1.1749, Val Accuracy: 0.7188
Epoch 9974/10000, Train Loss: 1.0196, Train Accuracy: 0.8940, Val Loss: 1.1749, Val Accuracy: 0.7188
Epoch 9975/10000, Train Loss: 1.0227, Train Accuracy: 0.8862, Val Loss: 1.1748, Val Accuracy: 0.7232
Epoch 9976/10000, Train Loss: 1.0279, Train Accuracy: 0.8850, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9977/10000, Train Loss: 1.0136, Train Accuracy: 0.8984, Val Loss: 1.1746, Val Accuracy: 0.7188
Epoch 9978/10000, Train Loss: 1.0192, Train Accuracy: 0.8940, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9979/10000, Train Loss: 1.0173, Train Accuracy: 0.8984, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9980/10000, Train Loss: 1.0206, Train Accuracy: 0.8884, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9981/10000, Train Loss: 1.0154, Train Accuracy: 0.9007, Val Loss: 1.1747, Val Accuracy: 0.7232
Epoch 9982/10000, Train Loss: 1.0134, Train Accuracy: 0.9007, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9983/10000, Train Loss: 1.0073, Train Accuracy: 0.9029, Val Loss: 1.1743, Val Accuracy: 0.7277
Epoch 9984/10000, Train Loss: 1.0190, Train Accuracy: 0.8917, Val Loss: 1.1744, Val Accuracy: 0.7232
Epoch 9985/10000, Train Loss: 1.0304, Train Accuracy: 0.8783, Val Loss: 1.1743, Val Accuracy: 0.7232
Epoch 9986/10000, Train Loss: 1.0153, Train Accuracy: 0.8951, Val Loss: 1.1745, Val Accuracy: 0.7232
Epoch 9987/10000, Train Loss: 1.0243, Train Accuracy: 0.8828, Val Loss: 1.1743, Val Accuracy: 0.7232
Epoch 9988/10000, Train Loss: 1.0157, Train Accuracy: 0.8973, Val Loss: 1.1740, Val Accuracy: 0.7232
Epoch 9989/10000, Train Loss: 1.0206, Train Accuracy: 0.8862, Val Loss: 1.1742, Val Accuracy: 0.7188
Epoch 9990/10000, Train Loss: 1.0164, Train Accuracy: 0.8951, Val Loss: 1.1743, Val Accuracy: 0.7188
Epoch 9991/10000, Train Loss: 1.0208, Train Accuracy: 0.8917, Val Loss: 1.1741, Val Accuracy: 0.7188
Epoch 9992/10000, Train Loss: 1.0256, Train Accuracy: 0.8862, Val Loss: 1.1741, Val Accuracy: 0.7188
Epoch 9993/10000, Train Loss: 1.0154, Train Accuracy: 0.9029, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9994/10000, Train Loss: 1.0026, Train Accuracy: 0.9107, Val Loss: 1.1744, Val Accuracy: 0.7188
Epoch 9995/10000, Train Loss: 1.0172, Train Accuracy: 0.8895, Val Loss: 1.1741, Val Accuracy: 0.7188
Epoch 9996/10000, Train Loss: 1.0224, Train Accuracy: 0.8940, Val Loss: 1.1739, Val Accuracy: 0.7188
Epoch 9997/10000, Train Loss: 1.0237, Train Accuracy: 0.8940, Val Loss: 1.1740, Val Accuracy: 0.7188
Epoch 9998/10000, Train Loss: 1.0233, Train Accuracy: 0.8906, Val Loss: 1.1738, Val Accuracy: 0.7188
Epoch 9999/10000, Train Loss: 1.0288, Train Accuracy: 0.8806, Val Loss: 1.1734, Val Accuracy: 0.7188
Epoch 10000/10000, Train Loss: 1.0230, Train Accuracy: 0.8850, Val Loss: 1.1733, Val Accuracy: 0.7188

torch.save(model_nn.state_dict(), best_model_path_nn)

# Load the best model
model_nn.load_state_dict(torch.load(best_model_path_nn))

<All keys matched successfully>

# Evaluate on test data
model_nn.eval()
X_test_tensor = torch.tensor(X_test.values, dtype=torch.float32)
y_test_tensor = torch.tensor(y_test.values, dtype=torch.long)  # Use long for class indices

with torch.no_grad():
    test_output = model_nn(X_test_tensor)
    test_loss = criterion(test_output, y_test_tensor)
    test_predictions = torch.argmax(test_output, dim=1)  # Get the predicted class indices
    test_correct = (test_predictions == y_test_tensor).sum().item()
    test_total = y_test_tensor.size(0)
    test_acc = test_correct / test_total

print(f'Test Loss: {test_loss.item():.4f}, Test Accuracy: {test_acc:.4f}')

Test Loss: 1.1447, Test Accuracy: 0.7500

anonymous_data = pd.read_csv('mldata_0003195463/mldata_0003195463.TEST_FEATURES.csv', index_col=0)
anonymous_data

final_an_predictions = best_rf_bayes.predict(anonymous_data)

# check the predictions respect the format, etc
final_an_predictions, len(final_an_predictions), set(final_an_predictions)

(array([0, 1, 0, ..., 1, 0, 1]), 1400, {0, 1, 2, 3, 4})

# let try now with the KNN best model to see how many similar predictions we get
final_an_predictions_knn = best_knn_grid.predict(anonymous_data)

final_an_predictions_knn, len(final_an_predictions_knn), set(final_an_predictions_knn)

(array([0, 1, 0, ..., 1, 0, 1]), 1400, {0, 1, 2, 3, 4})

k=0
for i in range(1400):
    if final_an_predictions[i]!=final_an_predictions_knn[i]:
        k=k+1
print("RF VS KNN", "\nnumber errors: ", k, "\npercentage correspondance: ", (1400-k)/1400)

RF VS KNN 
number errors:  317 
percentage correspondance:  0.7735714285714286

np.savetxt('test_predictions_Federico_Pezzoli_ML_Project.txt', final_an_predictions, fmt='%d')

	label	feature_1	feature_2	feature_3	feature_4	feature_5	feature_6	feature_7	feature_8	feature_9	...	feature_16	feature_17	feature_18	feature_19	feature_20	feature_21	feature_22	feature_23	feature_24	feature_25
0	0	0.880273	0.442573	-2.032819	-0.576659	-4.358051	2.376050	0.878844	0.880273	-1.874594	...	5.111025	-3.170193	-1.846344	6.816500	-0.325096	0.356847	0.267963	0.128522	4.710026	2.439719
1	1	1.313825	-1.949632	1.070599	1.394479	-0.059726	-2.975673	3.306127	1.313825	4.609667	...	-4.540766	-4.718089	-0.490495	3.271247	0.120484	0.388111	0.166516	1.187520	-4.999382	2.578916
2	0	-1.009061	-0.301009	5.641678	-0.921311	-2.646763	-1.947697	-0.578194	-1.009061	1.917913	...	0.663454	0.724729	0.229717	2.032490	0.905951	0.175052	-2.693749	-3.747243	5.988060	2.321502
3	0	-0.239631	3.031876	-1.614844	-1.091440	-0.776343	0.390649	-0.113804	-0.239631	-2.506136	...	5.037567	0.179098	-1.320429	3.930034	0.073331	-1.778206	-0.786323	-2.204570	5.601020	-0.230172
4	3	2.612405	0.535401	-0.396174	0.251268	4.729981	1.030001	-2.412348	2.612405	3.542474	...	-2.521146	-0.048739	-0.010981	-6.330675	1.710562	-0.306278	0.112979	2.182430	-4.726831	-1.039056
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1395	4	1.658674	-2.182582	1.361128	-0.223131	1.381046	1.378637	1.010512	1.658674	0.911761	...	-3.797807	1.035576	3.116603	-3.478307	-2.576972	1.423271	-0.985356	-1.662373	0.367540	1.185928
1396	3	1.343677	-0.084420	-0.678494	1.063410	2.486721	2.675759	0.063485	1.343677	6.019151	...	2.674485	2.995162	-0.128158	-3.063000	-3.342745	-1.010822	-1.358623	1.126761	-5.258127	-0.244412
1397	0	-1.199296	4.393630	0.087376	-0.706097	2.294865	-0.709506	-1.220693	-1.199296	0.552521	...	-0.104632	3.663284	0.118288	6.718347	3.372529	-0.066236	-0.165354	-0.497060	8.260052	5.352153
1398	3	0.444458	-5.569485	-2.959195	-0.197783	-1.033010	-0.518803	3.340311	0.444458	0.795092	...	3.725220	-2.332213	0.650232	5.851846	6.574953	1.820581	-0.218203	0.403429	-3.459758	0.700423
1399	4	-0.160659	1.186228	-1.238557	-1.203545	0.084697	-0.178147	0.750582	-0.160659	-0.904650	...	4.180642	0.364106	1.047320	0.269967	-0.071741	0.273339	-1.399230	-2.708364	0.516151	-1.190896

	feature_1	feature_2	feature_3	feature_4	feature_5	feature_6	feature_7	feature_8	feature_9	feature_10	...	feature_16	feature_17	feature_18	feature_19	feature_20	feature_21	feature_22	feature_23	feature_24	feature_25
0	0.880273	0.442573	-2.032819	-0.576659	-4.358051	2.376050	0.878844	0.880273	-1.874594	0.244483	...	5.111025	-3.170193	-1.846344	6.816500	-0.325096	0.356847	0.267963	0.128522	4.710026	2.439719
1	1.313825	-1.949632	1.070599	1.394479	-0.059726	-2.975673	3.306127	1.313825	4.609667	0.376011	...	-4.540766	-4.718089	-0.490495	3.271247	0.120484	0.388111	0.166516	1.187520	-4.999382	2.578916
2	-1.009061	-0.301009	5.641678	-0.921311	-2.646763	-1.947697	-0.578194	-1.009061	1.917913	-0.108523	...	0.663454	0.724729	0.229717	2.032490	0.905951	0.175052	-2.693749	-3.747243	5.988060	2.321502
3	-0.239631	3.031876	-1.614844	-1.091440	-0.776343	0.390649	-0.113804	-0.239631	-2.506136	0.492805	...	5.037567	0.179098	-1.320429	3.930034	0.073331	-1.778206	-0.786323	-2.204570	5.601020	-0.230172
4	2.612405	0.535401	-0.396174	0.251268	4.729981	1.030001	-2.412348	2.612405	3.542474	1.402761	...	-2.521146	-0.048739	-0.010981	-6.330675	1.710562	-0.306278	0.112979	2.182430	-4.726831	-1.039056
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1395	1.658674	-2.182582	1.361128	-0.223131	1.381046	1.378637	1.010512	1.658674	0.911761	0.310275	...	-3.797807	1.035576	3.116603	-3.478307	-2.576972	1.423271	-0.985356	-1.662373	0.367540	1.185928
1396	1.343677	-0.084420	-0.678494	1.063410	2.486721	2.675759	0.063485	1.343677	6.019151	1.785352	...	2.674485	2.995162	-0.128158	-3.063000	-3.342745	-1.010822	-1.358623	1.126761	-5.258127	-0.244412
1397	-1.199296	4.393630	0.087376	-0.706097	2.294865	-0.709506	-1.220693	-1.199296	0.552521	0.732084	...	-0.104632	3.663284	0.118288	6.718347	3.372529	-0.066236	-0.165354	-0.497060	8.260052	5.352153
1398	0.444458	-5.569485	-2.959195	-0.197783	-1.033010	-0.518803	3.340311	0.444458	0.795092	0.008757	...	3.725220	-2.332213	0.650232	5.851846	6.574953	1.820581	-0.218203	0.403429	-3.459758	0.700423
1399	-0.160659	1.186228	-1.238557	-1.203545	0.084697	-0.178147	0.750582	-0.160659	-0.904650	0.409299	...	4.180642	0.364106	1.047320	0.269967	-0.071741	0.273339	-1.399230	-2.708364	0.516151	-1.190896

	0	1	2	3	4	5	6	7	8	9	...	1390	1391	1392	1393	1394	1395	1396	1397	1398	1399
feature_1	0.880273	1.313825	-1.009061	-0.239631	2.612405	0.037314	2.010636	1.986206	0.006886	-4.488281	...	-0.820145	-1.729645	-1.317473	0.091772	0.937398	1.658674	1.343677	-1.199296	0.444458	-0.160659
feature_2	0.442573	-1.949632	-0.301009	3.031876	0.535401	-0.206636	0.621676	4.117393	-0.548541	0.012253	...	-0.837771	-0.531008	-2.375530	-0.624140	3.415699	-2.182582	-0.084420	4.393630	-5.569485	1.186228
feature_3	-2.032819	1.070599	5.641678	-1.614844	-0.396174	3.805659	-5.766030	-2.116423	-1.114819	0.168275	...	3.147020	3.084188	0.452407	1.703822	0.193878	1.361128	-0.678494	0.087376	-2.959195	-1.238557
feature_4	-0.576659	1.394479	-0.921311	-1.091440	0.251268	-1.248468	-0.060257	-1.030494	-1.044195	0.713612	...	1.044003	-0.132301	0.586763	1.752429	0.932712	-0.223131	1.063410	-0.706097	-0.197783	-1.203545
feature_5	-4.358051	-0.059726	-2.646763	-0.776343	4.729981	-2.630187	-2.617304	1.891215	0.281889	0.010156	...	-1.181065	1.801259	0.754335	-1.361584	-1.184189	1.381046	2.486721	2.294865	-1.033010	0.084697
feature_6	2.376050	-2.975673	-1.947697	0.390649	1.030001	-3.808977	-2.106621	1.333070	-0.888954	1.291766	...	-0.374998	-0.245327	-1.686892	-0.029591	2.938863	1.378637	2.675759	-0.709506	-0.518803	-0.178147
feature_7	0.878844	3.306127	-0.578194	-0.113804	-2.412348	-1.709104	-1.109602	0.912973	2.562891	-3.332946	...	-0.040821	-1.421910	1.144027	-0.310815	-2.194036	1.010512	0.063485	-1.220693	3.340311	0.750582
feature_8	0.880273	1.313825	-1.009061	-0.239631	2.612405	0.037314	2.010636	1.986206	0.006886	-4.488281	...	-0.820145	-1.729645	-1.317473	0.091772	0.937398	1.658674	1.343677	-1.199296	0.444458	-0.160659
feature_9	-1.874594	4.609667	1.917913	-2.506136	3.542474	-1.901907	4.176352	-0.352365	3.993937	1.284281	...	0.234835	3.096202	1.827541	-1.202440	-1.212045	0.911761	6.019151	0.552521	0.795092	-0.904650
feature_10	0.244483	0.376011	-0.108523	0.492805	1.402761	0.205311	-1.246551	-0.286358	-0.215466	0.141398	...	0.040927	-3.070705	0.748908	1.509786	-1.360279	0.310275	1.785352	0.732084	0.008757	0.409299
feature_11	-0.568563	-0.642429	0.631918	0.123358	2.102372	1.804765	1.085559	-3.084630	-2.913143	-1.486520	...	-0.726145	-0.587255	-1.274088	-1.070924	0.271354	1.427420	2.612296	3.378662	4.065548	-2.006805
feature_12	-3.958259	0.527434	-0.905757	-2.559503	1.169881	-0.072967	2.088462	0.505836	-0.547933	0.655720	...	1.250022	1.936665	-0.652181	-1.301670	-2.924451	2.547526	-2.583972	1.055483	1.847198	-1.156191
feature_13	0.846233	2.406618	1.901215	0.814844	-1.005312	0.698838	-0.779006	1.718272	-0.721186	-0.566567	...	-0.519731	0.077736	0.463265	-0.280210	-0.898018	-0.200645	2.611102	-0.742559	1.279831	-0.801016
feature_14	7.906497	1.275940	-3.975294	2.398946	-0.229136	-6.634834	-2.048398	2.433992	1.326202	-1.058776	...	-6.728930	-1.992863	4.801895	2.404796	1.975635	5.183851	5.040128	-6.805083	-1.076242	2.433056
feature_15	0.835684	1.206942	0.301467	0.399737	0.584454	0.864146	1.552834	0.685178	0.373199	0.245434	...	0.176876	-0.351053	1.137664	-0.453112	1.490879	-0.608051	0.951184	-0.138551	-0.193516	1.036109
feature_16	5.111025	-4.540766	0.663454	5.037567	-2.521146	-3.521657	0.749332	-0.438854	2.135337	4.407460	...	-0.142716	-1.753790	1.048744	2.699760	5.922917	-3.797807	2.674485	-0.104632	3.725220	4.180642
feature_17	-3.170193	-4.718089	0.724729	0.179098	-0.048739	0.117485	-0.813414	0.704341	-2.462587	1.933163	...	5.272173	0.910549	-1.522661	0.720169	2.059841	1.035576	2.995162	3.663284	-2.332213	0.364106
feature_18	-1.846344	-0.490495	0.229717	-1.320429	-0.010981	-1.109924	-1.336012	0.464369	0.758567	-0.225195	...	-0.855814	1.083912	0.278338	-0.190353	0.782890	3.116603	-0.128158	0.118288	0.650232	1.047320
feature_19	6.816500	3.271247	2.032490	3.930034	-6.330675	4.948475	2.291858	-1.472067	0.506498	-5.468823	...	-1.680982	-2.708883	0.817680	-0.767239	3.523459	-3.478307	-3.063000	6.718347	5.851846	0.269967
feature_20	-0.325096	0.120484	0.905951	0.073331	1.710562	2.633378	-4.093771	-1.642073	0.468107	-2.921080	...	0.477611	0.881359	-0.255975	0.046852	2.957629	-2.576972	-3.342745	3.372529	6.574953	-0.071741
feature_21	0.356847	0.388111	0.175052	-1.778206	-0.306278	1.346645	0.430862	0.550580	-0.063203	-0.045571	...	0.076906	-1.118559	-0.590103	-0.474936	-1.266574	1.423271	-1.010822	-0.066236	1.820581	0.273339
feature_22	0.267963	0.166516	-2.693749	-0.786323	0.112979	-0.104546	-1.004232	-0.073920	-0.658809	1.797368	...	0.361732	1.181771	-1.922470	-0.146421	0.140574	-0.985356	-1.358623	-0.165354	-0.218203	-1.399230
feature_23	0.128522	1.187520	-3.747243	-2.204570	2.182430	-0.415033	-1.703285	0.336433	0.068914	-3.230154	...	-0.143410	-1.786970	-2.884640	-3.145130	-1.840632	-1.662373	1.126761	-0.497060	0.403429	-2.708364
feature_24	4.710026	-4.999382	5.988060	5.601020	-4.726831	9.718475	0.445922	-1.713812	-7.775547	-0.546823	...	0.489176	0.156532	-0.578978	3.531062	8.763727	0.367540	-5.258127	8.260052	-3.459758	0.516151
feature_25	2.439719	2.578916	2.321502	-0.230172	-1.039056	1.988640	-3.537702	-0.325273	0.068403	-1.991403	...	-0.214643	3.283793	1.946495	-0.301800	3.841910	1.185928	-0.244412	5.352153	0.700423	-1.190896

	0	1	2	3	4	5	6	7	8	9	...	1390	1391	1392	1393	1394	1395	1396	1397	1398	1399
count	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	...	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000	25.000000
mean	0.656437	0.245523	0.143659	0.280489	0.222108	0.193688	-0.430322	0.283592	-0.255867	-0.687581	...	-0.100641	-0.066638	-0.014816	0.115674	1.128262	0.409728	0.681583	1.056996	0.575765	-0.025159
std	3.019691	2.471941	2.401257	2.181782	2.428479	3.143410	2.265609	1.621682	2.123480	2.302009	...	1.980072	1.803538	1.653497	1.468609	2.691906	2.049268	2.594289	3.091477	2.746377	1.426685
min	-4.358051	-4.999382	-3.975294	-2.559503	-6.330675	-6.634834	-5.766030	-3.084630	-7.775547	-5.468823	...	-6.728930	-3.070705	-2.884640	-3.145130	-2.924451	-3.797807	-5.258127	-6.805083	-5.569485	-2.708364
25%	-0.576659	-0.490495	-1.009061	-1.091440	-0.396174	-1.248468	-1.703285	-0.438854	-0.721186	-1.991403	...	-0.820145	-1.729645	-1.317473	-0.624140	-1.184189	-0.608051	-0.678494	-0.706097	-0.518803	-1.156191
50%	0.356847	0.527434	0.175052	-0.113804	0.251268	0.037314	-0.779006	0.464369	0.006886	-0.045571	...	-0.142716	-0.245327	0.278338	-0.190353	0.932712	1.010512	1.063410	0.087376	0.444458	-0.071741
75%	0.880273	1.313825	0.905951	0.492805	1.710562	1.346645	1.085559	1.333070	0.468107	0.655720	...	0.361732	1.083912	0.817680	0.720169	2.938863	1.423271	2.611102	3.372529	1.820581	0.516151
max	7.906497	4.609667	5.988060	5.601020	4.729981	9.718475	4.176352	4.117393	3.993937	4.407460	...	5.272173	3.283793	4.801895	3.531062	8.763727	5.183851	6.019151	8.260052	6.574953	4.180642

	feature_1	feature_2	feature_3	feature_4	feature_5	feature_6	feature_7	feature_8	feature_9	feature_10	...	feature_16	feature_17	feature_18	feature_19	feature_20	feature_21	feature_22	feature_23	feature_24	feature_25
count	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	...	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000	1400.000000
mean	0.210835	0.612782	-0.082197	0.185904	0.070735	-0.359291	-0.115731	0.210835	0.198517	0.050355	...	-0.099482	0.683999	0.109756	1.089425	0.018756	0.118668	0.079930	-0.132304	1.543277	0.571845
std	2.195976	2.395809	2.358706	1.024291	2.418231	2.192464	2.295636	2.195976	2.305057	0.992986	...	4.080395	2.303319	1.037643	4.646323	2.226349	1.017631	1.008222	2.360151	4.888676	2.287947
min	-6.459859	-7.795962	-7.704676	-2.948682	-8.315868	-7.448146	-7.183413	-6.459859	-7.387299	-4.282637	...	-15.063160	-7.019747	-3.042580	-14.004747	-6.790704	-3.025071	-3.247761	-8.358437	-15.669281	-6.603355
25%	-1.350847	-0.870054	-1.739086	-0.516367	-1.465739	-1.849062	-1.747100	-1.350847	-1.347676	-0.634657	...	-2.902051	-0.868773	-0.632218	-2.030589	-1.463973	-0.555009	-0.580996	-1.643818	-1.626720	-0.823231
50%	0.180684	0.673686	-0.099358	0.200757	0.039412	-0.356757	-0.160878	0.180684	0.024433	0.051986	...	-0.170632	0.718832	0.107171	1.124641	0.043266	0.109773	0.110199	-0.206132	1.608067	0.653977
75%	1.768125	2.209933	1.563456	0.895352	1.709264	1.122682	1.347230	1.768125	1.651034	0.700098	...	2.751130	2.251132	0.825007	4.141713	1.460704	0.752059	0.709252	1.444386	4.824556	2.188991
max	8.326302	7.934452	8.604717	3.300430	8.083031	6.043853	9.691771	8.326302	10.334941	4.228823	...	14.220578	8.859061	3.351073	15.998109	8.324109	4.014849	3.563236	9.232769	19.603832	7.851396

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	importance
feature_20	0.062109
feature_19	0.057101
feature_11	0.055179
feature_9	0.053888
feature_3	0.052883
feature_7	0.051550
feature_17	0.047547
feature_6	0.044916
feature_12	0.044347
feature_25	0.043836
feature_24	0.042901
feature_16	0.042853
feature_2	0.041756
feature_8	0.041355
feature_1	0.040886
feature_14	0.040595
feature_5	0.038976
feature_23	0.038294
feature_4	0.023685
feature_15	0.023309
feature_10	0.023308
feature_18	0.022646
feature_13	0.022306
feature_21	0.022169
feature_22	0.021603

	feature_1	feature_2	feature_3	feature_4	feature_5	feature_6	feature_7	feature_8	feature_9	feature_10	...	feature_16	feature_17	feature_18	feature_19	feature_20	feature_21	feature_22	feature_23	feature_24	feature_25
id
0	-1.583901	0.066270	0.462274	-0.175453	-0.122860	-2.964932	-1.128756	-1.583901	-0.837369	-1.541634	...	2.058315	1.987120	0.875662	0.490501	-0.564009	-0.473025	-3.121843	-3.204708	4.059989	-1.230859
1	0.741998	0.842662	-0.580674	1.177410	-1.590579	-0.992677	1.202091	0.741998	0.397817	0.878938	...	-2.693609	2.358702	-0.448296	1.258434	-0.929838	0.551937	1.675974	2.500228	-1.905566	0.004239
2	-2.690293	-1.274130	3.564006	0.840850	-1.267567	-0.168341	2.832282	-2.690293	-2.031966	1.289001	...	5.708247	-1.422307	0.561772	5.098278	2.644700	-0.522982	0.559692	-2.000696	2.440799	0.144461
3	-1.449382	1.068814	-3.820457	-0.836199	-1.242546	-1.803914	0.858350	-1.449382	-3.473241	1.331370	...	1.037856	-3.569374	0.000523	4.939084	-2.669314	-0.229439	-1.235043	-2.255308	4.259756	0.219297
4	-0.001136	4.266773	0.390607	-0.230595	0.055867	-0.388356	0.298274	-0.001136	2.720829	0.960466	...	-1.661571	2.500116	0.314138	2.876392	0.793374	0.016719	-1.138375	0.867594	0.588746	1.752658
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
1395	3.051612	5.335903	-0.780311	-1.206728	6.041506	-2.462116	-0.099222	3.051612	-0.541221	0.031599	...	-2.389265	-1.532996	0.165623	-0.557866	2.452305	-1.016575	-0.347464	-4.107339	4.148608	-0.819975
1396	-0.818027	0.131502	-3.361555	0.574756	-1.395142	-2.137571	2.059778	-0.818027	4.986959	0.337357	...	2.695408	-2.043497	0.417200	4.119033	-1.835029	-1.014946	0.459286	0.252998	-5.875338	-0.483199
1397	1.300382	4.959589	-0.821422	0.048367	-1.133989	2.583393	3.246328	1.300382	1.914509	0.360079	...	0.811838	4.422174	-1.072638	4.729813	-2.414941	1.112228	0.541504	1.608467	-0.122532	0.698078
1398	-3.811468	-0.570010	0.967775	-0.904938	-2.729183	-3.508922	0.989772	-3.811468	-2.331983	1.343327	...	-1.978188	0.218630	0.657534	6.934419	1.609578	-1.178043	-0.004904	3.420006	1.526097	-0.750451
1399	2.115240	3.851803	-0.699010	-1.335313	-0.850509	0.122552	1.786011	2.115240	0.213781	-1.410630	...	-1.658974	1.958692	0.723056	6.628800	-1.487204	0.189379	-0.214925	1.151181	5.037282	1.696641